1. Wprowadzenie
Projekt dotyczy analizy danych klientów sklepu rowerowego. Wykorzystano język R oraz liczne pakiety analityczne, takie jak tidyverse, dlookr, validate czy VIM. Celem było sprawdzenie struktury danych, analiza braków, walidacja oraz imputacja brakujących wartości. Dodatkowo przeprowadzono wizualizację zależności między zmiennymi.
Ładowanie danych
Ładowanie pakietów
Sprawdzenie struktury danych
str(sklep_rowerowy)## spc_tbl_ [1,000 × 13] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ id : num [1:1000] 12496 24107 14177 24381 25597 ...
## $ marital_status : chr [1:1000] "Married" "Married" "Married" "Single" ...
## $ gender : chr [1:1000] "Female" "Male" "Male" NA ...
## $ income : num [1:1000] 40000 30000 80000 70000 30000 10000 160000 40000 20000 NA ...
## $ children : num [1:1000] 1 3 5 0 0 2 2 1 2 2 ...
## $ education : chr [1:1000] "Bachelors" "Partial College" "Partial College" "Bachelors" ...
## $ occupation : chr [1:1000] "Skilled Manual" "Clerical" "Professional" "Professional" ...
## $ home_owner : chr [1:1000] "Yes" "Yes" "No" "Yes" ...
## $ cars : num [1:1000] 0 1 2 1 0 0 4 0 2 1 ...
## $ commute_distance: chr [1:1000] "0-1 Miles" "0-1 Miles" "2-5 Miles" "5-10 Miles" ...
## $ region : chr [1:1000] "Europe" "Europe" "Europe" "Pacific" ...
## $ age : num [1:1000] 42 43 60 41 36 50 33 43 58 NA ...
## $ purchased_bike : chr [1:1000] "No" "No" "No" "Yes" ...
## - attr(*, "spec")=
## .. cols(
## .. ID = col_double(),
## .. `Marital Status` = col_character(),
## .. Gender = col_character(),
## .. Income = col_double(),
## .. Children = col_double(),
## .. Education = col_character(),
## .. Occupation = col_character(),
## .. `Home Owner` = col_character(),
## .. Cars = col_double(),
## .. `Commute Distance` = col_character(),
## .. Region = col_character(),
## .. Age = col_double(),
## .. `Purchased Bike` = col_character()
## .. )
## - attr(*, "problems")=<externalptr>typy_danych <- sapply(sklep_rowerowy,class)
print(typy_danych)## id marital_status gender income
## "numeric" "character" "character" "numeric"
## children education occupation home_owner
## "numeric" "character" "character" "character"
## cars commute_distance region age
## "numeric" "character" "character" "numeric"
## purchased_bike
## "character"Opis zmiennych
id (numeric) – Unikalny identyfikator klienta.
marital_status (character) – Status cywilny klienta (np. “Single”, “Married”).
gender (character) – Płeć klienta (np. “Male”, “Female”).
income (numeric) – Dochód klienta w jednostkach walutowych.
children (numeric) – Liczba dzieci klienta.
education (character) – Poziom wykształcenia klienta (np. “Bachelors”, “PhD”).
occupation (character) – Zawód lub sektor, w którym pracuje klient (np. “Engineer”, “Doctor”).
home_owner (character) – Informacja, czy klient jest właścicielem domu (np. “Yes”, “No”).
cars (numeric) – Liczba samochodów posiadanych przez klienta.
commute_distance (character) – Typowa odległość dojazdu do pracy (np. “0-1 Miles”, “10+ Miles”).
region (character) – Region zamieszkania klienta (np. “Europe”, “North America”).
age (numeric) – Wiek klienta.
purchased_bike (character) – Informacja, czy klient kupił rower (“Yes”, “No”).
Analiza braków danych
Wykorzystując pakiet “naniar” ustalamy czy w wśród naszych danych znajdują się braki danych.
Instalacja pakietu
# install.packages("naniar")
library(naniar)## Warning: pakiet 'naniar' został zbudowany w wersji R 4.4.2##
## Dołączanie pakietu: 'naniar'## Następujący obiekt został zakryty z 'package:validate':
##
## all_completeZliczanie całkowitej liczby braków
n_miss(sklep_rowerowy)## [1] 53Są 53 braki w zbiorze danych.
Zliczanie całkowitej liczby kompletnych wartości
n_complete(sklep_rowerowy)## [1] 12947Liczba całkowitych wartości - bez brakujących wartości to 12947.
Procent braków
prop_miss(sklep_rowerowy)## [1] 0.004076923Wśród zbioru danych brakujące wartości to około 0,41% odnośnie do liczby wszystkich wartości.
Tabela podsumowująca braki w zbiorze danych
miss_var_summary(sklep_rowerowy)## # A tibble: 13 × 3
## variable n_miss pct_miss
## <chr> <int> <num>
## 1 gender 11 1.1
## 2 cars 9 0.9
## 3 children 8 0.8
## 4 age 8 0.8
## 5 marital_status 7 0.7
## 6 income 6 0.6
## 7 home_owner 4 0.4
## 8 id 0 0
## 9 education 0 0
## 10 occupation 0 0
## 11 commute_distance 0 0
## 12 region 0 0
## 13 purchased_bike 0 0#Największa ilosć braków znajduje się w kolumnie “Gender”. Braki znajdują się w 7 kolumnach z 12.
Wizualizacja braków
vis_miss(sklep_rowerowy)
# Przekroje braków
gg_miss_upset(sklep_rowerowy,
nsets=53)
# Wniosek: Najwięcej braków dotyczy zmiennych mówiących o edukacji,
dochodach oraz stanowisku pracy.
#Reguły do wszystkich numerycznych zmiennych
reguły <- editset(c(
"Age>=1",
"Age<=120",
"Income>=0",
"Children>=0",
"Children<=5",
"Cars>=0",
"Cars<=10",
"Children>=0",
"Children<=5"
))
print(reguły)##
## Edit set:
## num1 : 1 <= Age
## num2 : Age <= 120
## num3 : 0 <= Income
## num4 : 0 <= Children
## num5 : Children <= 5
## num6 : 0 <= Cars
## num7 : Cars <= 10
## num8 : 0 <= Children
## num9 : Children <= 52. Walidacja danych
#Za pomocą walidacji danych sprawdzamy czy spełnione zostały nasze założenia
#Instalowanie pakietu “validate”
library(validate)Sprawdzenie wartości jakie są w zbiorze danych
glimpse(sklep_rowerowy)## Rows: 1,000
## Columns: 13
## $ id <dbl> 12496, 24107, 14177, 24381, 25597, 13507, 27974, 1936…
## $ marital_status <chr> "Married", "Married", "Married", "Single", "Single", …
## $ gender <chr> "Female", "Male", "Male", NA, "Male", "Female", "Male…
## $ income <dbl> 40000, 30000, 80000, 70000, 30000, 10000, 160000, 400…
## $ children <dbl> 1, 3, 5, 0, 0, 2, 2, 1, 2, 2, 3, 0, 5, 2, 1, 2, 3, 1,…
## $ education <chr> "Bachelors", "Partial College", "Partial College", "B…
## $ occupation <chr> "Skilled Manual", "Clerical", "Professional", "Profes…
## $ home_owner <chr> "Yes", "Yes", "No", "Yes", "No", "Yes", NA, "Yes", "Y…
## $ cars <dbl> 0, 1, 2, 1, 0, 0, 4, 0, 2, 1, 2, 4, NA, 1, 1, 1, 2, 0…
## $ commute_distance <chr> "0-1 Miles", "0-1 Miles", "2-5 Miles", "5-10 Miles", …
## $ region <chr> "Europe", "Europe", "Europe", "Pacific", "Europe", "E…
## $ age <dbl> 42, 43, 60, 41, 36, 50, 33, 43, 58, NA, 54, 36, 55, 3…
## $ purchased_bike <chr> "No", "No", "No", "Yes", "Yes", "No", "Yes", "Yes", "…Dane z stanem cywilnym, dochodem, płcią i posiadaniem domu
wynik_reguly<-check_that(sklep_rowerowy,Marital.status==Married,Income>=70000)
wynik_reguly## Object of class 'validation'
## Call:
## check_that(sklep_rowerowy, Marital.status == Married, Income >=
## 70000)
##
## Rules confronted: 2
## With fails : 0
## With missings: 0
## Threw warning: 0
## Threw error : 2wynik_reguly2<-check_that(sklep_rowerowy,Gender==Male, Home.Owner==Yes)
wynik_reguly2## Object of class 'validation'
## Call:
## check_that(sklep_rowerowy, Gender == Male, Home.Owner == Yes)
##
## Rules confronted: 2
## With fails : 0
## With missings: 0
## Threw warning: 0
## Threw error : 2summary(wynik_reguly)## name items passes fails nNA error warning
## 1 V1 0 0 0 0 TRUE FALSE
## 2 V2 0 0 0 0 TRUE FALSE
## expression
## 1 abs(Marital.status - Married) <= 1e-08
## 2 Income - 70000 >= -1e-08summary(wynik_reguly2)## name items passes fails nNA error warning expression
## 1 V1 0 0 0 0 TRUE FALSE abs(Gender - Male) <= 1e-08
## 2 V2 0 0 0 0 TRUE FALSE abs(Home.Owner - Yes) <= 1e-08Dane z edukacją, posiadaniem roweru, poziomem wykształcenia i zawodem
library(validate)
wynik_reguly3<-check_that(sklep_rowerowy,Region==Pacific,Purchased_Bike==Yes)
wynik_reguly3## Object of class 'validation'
## Call:
## check_that(sklep_rowerowy, Region == Pacific, Purchased_Bike ==
## Yes)
##
## Rules confronted: 2
## With fails : 0
## With missings: 0
## Threw warning: 0
## Threw error : 2wynik_reguly4<-check_that(sklep_rowerowy,Education==Bachelors,Occupation==Professional)
wynik_reguly4## Object of class 'validation'
## Call:
## check_that(sklep_rowerowy, Education == Bachelors, Occupation ==
## Professional)
##
## Rules confronted: 2
## With fails : 0
## With missings: 0
## Threw warning: 0
## Threw error : 2summary(wynik_reguly3)## name items passes fails nNA error warning expression
## 1 V1 0 0 0 0 TRUE FALSE abs(Region - Pacific) <= 1e-08
## 2 V2 0 0 0 0 TRUE FALSE abs(Purchased_Bike - Yes) <= 1e-08summary(wynik_reguly4)## name items passes fails nNA error warning
## 1 V1 0 0 0 0 TRUE FALSE
## 2 V2 0 0 0 0 TRUE FALSE
## expression
## 1 abs(Education - Bachelors) <= 1e-08
## 2 abs(Occupation - Professional) <= 1e-08Dane jako kobieta, edukacja, nie posiada domu, singiel
library(validate)
wynik_reguly5<-check_that(sklep_rowerowy,Gender==Female,Education==Graduate_Degree)
wynik_reguly5## Object of class 'validation'
## Call:
## check_that(sklep_rowerowy, Gender == Female, Education == Graduate_Degree)
##
## Rules confronted: 2
## With fails : 0
## With missings: 0
## Threw warning: 0
## Threw error : 2wynik_reguly6<-check_that(sklep_rowerowy,Home_Owner==No,Marital.status==Single)
wynik_reguly6## Object of class 'validation'
## Call:
## check_that(sklep_rowerowy, Home_Owner == No, Marital.status ==
## Single)
##
## Rules confronted: 2
## With fails : 0
## With missings: 0
## Threw warning: 0
## Threw error : 2summary(wynik_reguly5)## name items passes fails nNA error warning
## 1 V1 0 0 0 0 TRUE FALSE
## 2 V2 0 0 0 0 TRUE FALSE
## expression
## 1 abs(Gender - Female) <= 1e-08
## 2 abs(Education - Graduate_Degree) <= 1e-08summary(wynik_reguly6)## name items passes fails nNA error warning
## 1 V1 0 0 0 0 TRUE FALSE
## 2 V2 0 0 0 0 TRUE FALSE
## expression
## 1 abs(Home_Owner - No) <= 1e-08
## 2 abs(Marital.status - Single) <= 1e-083 Wypełnianie braków danych
#Instalowane potrzebnego pakietu
#install.packages("hot.deck")
#install.packages("VIM")
library(VIM)
library(hot.deck)## Warning: pakiet 'hot.deck' został zbudowany w wersji R 4.4.2#Imputacja
sklep_rowerowy <- hotdeck(sklep_rowerowy)
print(sklep_rowerowy)## id marital_status gender income children education
## 1 12496 Married Female 40000 1 Bachelors
## 2 24107 Married Male 30000 3 Partial College
## 3 14177 Married Male 80000 5 Partial College
## 4 24381 Single Female 70000 0 Bachelors
## 5 25597 Single Male 30000 0 Bachelors
## 6 13507 Married Female 10000 2 Partial College
## 7 27974 Single Male 160000 2 High School
## 8 19364 Married Male 40000 1 Bachelors
## 9 22155 Single Male 20000 2 Partial High School
## 10 19280 Married Male 40000 2 Partial College
## 11 22173 Married Female 30000 3 High School
## 12 12697 Single Female 90000 0 Bachelors
## 13 11434 Married Male 170000 5 Partial College
## 14 25323 Married Male 40000 2 Partial College
## 15 23542 Single Male 60000 1 Partial College
## 16 20870 Single Female 10000 2 High School
## 17 23316 Single Male 30000 3 Partial College
## 18 12610 Married Female 30000 1 Bachelors
## 19 27183 Single Male 40000 2 Partial College
## 20 25940 Single Male 20000 2 Partial High School
## 21 25598 Married Female 40000 0 Graduate Degree
## 22 21564 Single Female 80000 0 Bachelors
## 23 19193 Single Male 40000 2 Partial College
## 24 26412 Married Female 80000 5 High School
## 25 27184 Single Male 40000 2 Partial College
## 26 12590 Single Male 30000 1 Bachelors
## 27 17841 Single Male 30000 0 Partial College
## 28 18283 Married Female 100000 0 Bachelors
## 29 18299 Married Male 70000 5 Partial College
## 30 16466 Single Female 20000 0 Partial High School
## 31 19273 Married Female 20000 2 Partial College
## 32 22400 Married Male 10000 0 Partial College
## 33 20942 Single Female 20000 0 High School
## 34 18484 Single Male 80000 2 High School
## 35 12291 Single Male 90000 5 Partial College
## 36 28380 Single Female 10000 5 Partial High School
## 37 17891 Married Female 10000 2 Partial College
## 38 27832 Single Female 30000 0 Partial College
## 39 26863 Single Male 20000 0 High School
## 40 16259 Single Female 10000 4 Partial High School
## 41 27803 Single Female 30000 2 Partial College
## 42 14347 Single Female 40000 2 Bachelors
## 43 17703 Married Female 10000 1 Graduate Degree
## 44 17185 Married Female 170000 4 Partial College
## 45 29380 Married Female 20000 3 High School
## 46 23986 Married Female 20000 1 Bachelors
## 47 24466 Married Female 60000 1 Partial College
## 48 29097 Single Female 40000 2 Partial College
## 49 19487 Married Male 30000 2 Partial College
## 50 14939 Married Male 40000 0 Bachelors
## 51 13826 Single Female 30000 0 Partial College
## 52 20619 Single Male 80000 0 Bachelors
## 53 12558 Married Female 20000 1 Bachelors
## 54 24871 Single Female 90000 4 High School
## 55 17319 Single Female 70000 0 Bachelors
## 56 28906 Married Male 80000 4 High School
## 57 12808 Married Male 40000 0 Bachelors
## 58 20567 Married Male 130000 4 Partial College
## 59 25502 Married Female 40000 1 Bachelors
## 60 15580 Married Male 60000 2 Bachelors
## 61 24185 Single Female 10000 1 High School
## 62 19291 Single Female 10000 2 High School
## 63 16713 Married Male 40000 2 Bachelors
## 64 16185 Single Male 60000 4 Bachelors
## 65 14927 Married Female 30000 1 Bachelors
## 66 29337 Single Male 30000 2 Partial College
## 67 29355 Married Female 40000 0 Graduate Degree
## 68 25303 Single Male 30000 0 High School
## 69 14813 Single Female 20000 4 High School
## 70 16438 Married Female 10000 0 Partial High School
## 71 14238 Married Male 120000 0 Partial High School
## 72 16200 Single Female 10000 0 Partial High School
## 73 24857 Married Female 130000 3 High School
## 74 26956 Single Female 20000 0 Partial College
## 75 14517 Married Female 20000 3 High School
## 76 12678 Single Female 130000 4 High School
## 77 16188 Single Female 20000 0 Partial High School
## 78 27969 Married Male 80000 0 Bachelors
## 79 15752 Married Male 80000 2 High School
## 80 27745 Single Male 40000 2 Bachelors
## 81 20828 Married Female 30000 4 Graduate Degree
## 82 19461 Single Female 10000 4 Partial High School
## 83 26941 Married Male 30000 0 Bachelors
## 84 28412 Single Male 20000 0 High School
## 85 24485 Single Male 40000 2 Bachelors
## 86 16514 Single Male 10000 0 Partial College
## 87 17191 Single Male 130000 3 Partial College
## 88 19608 Married Male 80000 5 Bachelors
## 89 24119 Single Male 30000 0 Partial College
## 90 25458 Married Male 20000 1 High School
## 91 26886 Single Female 30000 0 Partial College
## 92 28436 Single Male 30000 0 Partial College
## 93 19562 Single Female 60000 2 Bachelors
## 94 15608 Single Female 30000 0 Partial College
## 95 16487 Single Female 30000 3 High School
## 96 17197 Single Female 90000 5 Partial College
## 97 12507 Married Male 30000 1 Partial College
## 98 23940 Married Male 40000 1 Bachelors
## 99 19441 Married Male 40000 0 Graduate Degree
## 100 26852 Married Female 20000 3 High School
## 101 12274 Single Male 10000 2 High School
## 102 20236 Single Male 60000 3 Bachelors
## 103 24149 Married Male 10000 2 Partial College
## 104 26139 Single Male 60000 1 Partial College
## 105 18491 Single Female 70000 2 High School
## 106 22707 Single Female 30000 0 Partial College
## 107 20430 Married Male 70000 2 Partial College
## 108 27494 Single Female 40000 2 Partial College
## 109 26829 Married Female 40000 0 Bachelors
## 110 28395 Single Male 40000 0 Bachelors
## 111 21006 Single Female 90000 1 Partial College
## 112 14682 Single Female 70000 0 Bachelors
## 113 17650 Single Female 40000 2 Partial College
## 114 29191 Single Female 130000 1 Graduate Degree
## 115 15030 Married Male 20000 0 Bachelors
## 116 24140 Single Male 10000 0 Graduate Degree
## 117 22496 Married Female 30000 1 Bachelors
## 118 24065 Single Female 20000 3 High School
## 119 19914 Married Male 80000 5 Bachelors
## 120 12871 Single Female 30000 0 Partial College
## 121 22988 Married Female 40000 2 Bachelors
## 122 15922 Married Male 150000 2 High School
## 123 12344 Single Female 80000 0 Bachelors
## 124 23627 Single Female 100000 3 Partial College
## 125 27775 Single Female 40000 0 Bachelors
## 126 29301 Married Male 80000 5 Bachelors
## 127 12716 Single Male 30000 0 Partial College
## 128 12472 Married Male 30000 1 Bachelors
## 129 20970 Single Male 10000 2 Partial College
## 130 26818 Single Male 10000 3 High School
## 131 12993 Married Male 60000 2 Bachelors
## 132 14192 Married Male 90000 4 High School
## 133 19477 Married Male 40000 0 Bachelors
## 134 26796 Single Male 40000 2 Bachelors
## 135 21094 Single Female 30000 2 Partial College
## 136 12234 Married Male 10000 2 Partial College
## 137 28683 Single Female 10000 1 High School
## 138 17994 Single Male 20000 2 High School
## 139 24273 Married Female 20000 2 Partial High School
## 140 26547 Single Female 30000 2 Partial College
## 141 22500 Single Male 40000 0 Bachelors
## 142 23993 Single Female 10000 0 Partial College
## 143 14832 Married Male 40000 1 Bachelors
## 144 16614 Married Female 80000 0 Bachelors
## 145 20877 Single Male 30000 1 Bachelors
## 146 20729 Married Female 40000 2 Partial College
## 147 22464 Married Male 40000 0 Graduate Degree
## 148 19475 Married Female 40000 0 Bachelors
## 149 19675 Married Male 20000 4 High School
## 150 12728 Single Male 30000 0 Partial College
## 151 26154 Single Male 60000 1 Partial College
## 152 29117 Single Male 100000 1 Bachelors
## 153 17845 Single Female 20000 0 Partial High School
## 154 25058 Married Male 100000 1 Bachelors
## 155 23426 Single Male 80000 5 Graduate Degree
## 156 14798 Single Female 10000 4 Partial High School
## 157 12664 Married Female 130000 5 Partial College
## 158 23979 Single Male 10000 2 Partial College
## 159 25605 Single Female 20000 2 Partial College
## 160 20797 Married Female 10000 1 Bachelors
## 161 21980 Single Female 60000 1 Bachelors
## 162 25460 Married Female 20000 2 High School
## 163 29181 Single Female 60000 2 Bachelors
## 164 24279 Single Male 40000 2 Partial College
## 165 22402 Married Male 10000 0 Partial College
## 166 15465 Married Female 10000 0 Partial College
## 167 26757 Single Male 90000 1 Bachelors
## 168 14233 Single Male 100000 0 High School
## 169 14058 Single Male 70000 0 Bachelors
## 170 12273 Married Male 30000 1 Bachelors
## 171 17203 Married Female 130000 4 Partial College
## 172 18144 Married Female 80000 5 Bachelors
## 173 23963 Married Male 10000 0 Partial High School
## 174 17907 Married Female 10000 0 Partial College
## 175 19442 Single Male 50000 0 Graduate Degree
## 176 17504 Single Female 80000 2 Partial College
## 177 12253 Single Female 20000 0 Partial College
## 178 27304 Single Female 110000 2 Partial College
## 179 14191 Married Male 160000 4 Partial College
## 180 12212 Married Female 10000 0 Graduate Degree
## 181 25529 Single Male 10000 1 Graduate Degree
## 182 22170 Married Female 30000 3 Partial College
## 183 19445 Married Female 10000 2 High School
## 184 15265 Single Male 40000 2 Bachelors
## 185 28918 Married Female 130000 4 High School
## 186 15799 Married Female 90000 1 Bachelors
## 187 11047 Married Female 30000 3 High School
## 188 18151 Single Male 80000 5 Partial College
## 189 20606 Married Female 70000 0 Bachelors
## 190 19482 Married Male 30000 1 Partial College
## 191 16489 Married Male 30000 3 High School
## 192 26944 Single Male 20000 2 High School
## 193 15682 Single Female 80000 5 Bachelors
## 194 26032 Married Female 70000 5 Bachelors
## 195 17843 Single Female 10000 0 Partial High School
## 196 25559 Single Male 20000 0 Bachelors
## 197 16209 Single Female 50000 0 Graduate Degree
## 198 11147 Married Male 60000 2 Graduate Degree
## 199 15214 Single Female 100000 0 Graduate Degree
## 200 11453 Single Male 80000 0 Bachelors
## 201 24584 Single Male 60000 0 Bachelors
## 202 12585 Married Male 10000 1 High School
## 203 18626 Single Male 40000 2 Partial College
## 204 29298 Single Female 60000 1 Partial College
## 205 24842 Single Female 90000 3 High School
## 206 15657 Married Male 30000 3 Graduate Degree
## 207 11415 Single Male 90000 5 Partial College
## 208 28729 Single Female 20000 0 Partial High School
## 209 22633 Single Female 40000 0 Graduate Degree
## 210 25649 Single Female 30000 3 Partial College
## 211 14669 Married Female 80000 4 Graduate Degree
## 212 19299 Married Female 50000 0 Graduate Degree
## 213 20946 Single Female 30000 0 Partial College
## 214 11451 Single Male 70000 0 Bachelors
## 215 25553 Married Male 30000 1 Bachelors
## 216 27951 Single Male 80000 4 Partial College
## 217 25026 Married Male 20000 2 Partial High School
## 218 13673 Single Female 20000 2 Partial High School
## 219 16043 Single Male 10000 1 Bachelors
## 220 22399 Single Male 10000 0 Partial College
## 221 27696 Married Male 60000 1 Bachelors
## 222 25313 Single Male 10000 0 Partial High School
## 223 13813 Married Female 30000 3 Partial College
## 224 18711 Single Female 70000 5 Bachelors
## 225 19650 Married Female 30000 2 Partial College
## 226 14135 Married Male 20000 1 Partial College
## 227 12833 Single Female 20000 3 High School
## 228 26849 Married Male 10000 3 Partial High School
## 229 20962 Married Female 20000 1 Graduate Degree
## 230 28915 Single Male 80000 5 High School
## 231 22830 Married Male 120000 4 Partial College
## 232 14777 Married Female 40000 0 Bachelors
## 233 12591 Married Female 30000 4 Graduate Degree
## 234 24174 Married Male 20000 0 Bachelors
## 235 24611 Married Male 90000 0 Bachelors
## 236 11340 Married Female 10000 1 Graduate Degree
## 237 25693 Single Female 30000 5 Graduate Degree
## 238 25555 Married Female 10000 0 Partial College
## 239 22006 Married Male 70000 5 Partial College
## 240 20060 Single Female 30000 0 High School
## 241 17702 Married Male 10000 1 Graduate Degree
## 242 12503 Single Female 30000 3 Partial College
## 243 23908 Single Male 30000 1 Bachelors
## 244 22527 Single Female 20000 0 High School
## 245 19057 Married Female 120000 3 Bachelors
## 246 18494 Married Male 110000 5 Bachelors
## 247 11249 Married Female 130000 3 Partial College
## 248 21568 Married Female 100000 0 High School
## 249 13981 Married Female 10000 5 High School
## 250 23432 Single Male 70000 0 Bachelors
## 251 22931 Married Male 100000 5 Graduate Degree
## 252 18172 Married Male 130000 4 High School
## 253 12666 Single Male 60000 0 Bachelors
## 254 20598 Married Male 100000 3 Partial High School
## 255 21375 Single Male 20000 2 Partial High School
## 256 20839 Single Female 30000 3 Graduate Degree
## 257 21738 Married Male 20000 1 Graduate Degree
## 258 14164 Single Female 50000 0 Graduate Degree
## 259 14193 Single Female 100000 3 Partial College
## 260 12705 Married Male 150000 0 Bachelors
## 261 22672 Single Female 30000 2 Partial College
## 262 26219 Married Female 40000 1 Bachelors
## 263 28468 Married Female 10000 2 Partial College
## 264 23419 Single Female 70000 5 Bachelors
## 265 17964 Married Male 40000 0 Graduate Degree
## 266 20919 Single Female 30000 2 Partial College
## 267 20927 Single Female 20000 5 High School
## 268 13133 Single Male 100000 5 Bachelors
## 269 19626 Married Male 70000 5 Partial College
## 270 21039 Single Female 50000 0 Graduate Degree
## 271 12231 Single Female 10000 2 Partial College
## 272 25665 Single Female 20000 0 High School
## 273 24061 Married Male 10000 4 Partial High School
## 274 26879 Single Female 20000 0 High School
## 275 12284 Married Female 30000 0 Bachelors
## 276 26654 Married Female 90000 1 Graduate Degree
## 277 14545 Married Female 10000 2 Partial College
## 278 24201 Married Female 10000 2 High School
## 279 20625 Married Male 100000 0 High School
## 280 16390 Single Male 30000 1 Bachelors
## 281 14804 Single Female 10000 3 Partial High School
## 282 12629 Single Male 20000 1 Partial College
## 283 14696 Single Male 10000 0 Partial High School
## 284 22005 Married Female 70000 5 Partial College
## 285 14544 Single Male 10000 1 Partial College
## 286 14312 Married Female 60000 1 Partial College
## 287 29120 Single Female 100000 1 Bachelors
## 288 24187 Single Female 30000 3 Graduate Degree
## 289 15758 Married Male 130000 0 Graduate Degree
## 290 29094 Married Male 30000 3 High School
## 291 28319 Single Female 60000 1 Partial College
## 292 16406 Married Male 40000 0 Bachelors
## 293 20923 Married Female 40000 1 Bachelors
## 294 11378 Single Female 10000 1 High School
## 295 20851 Single Male 20000 0 Partial College
## 296 21557 Single Female 110000 0 Partial College
## 297 26663 Single Female 60000 2 Bachelors
## 298 11896 Married Male 100000 1 Graduate Degree
## 299 14189 Married Female 90000 4 High School
## 300 13136 Married Female 30000 2 Partial College
## 301 25906 Single Female 10000 5 High School
## 302 17926 Single Female 70000 0 Bachelors
## 303 26928 Single Male 30000 1 Bachelors
## 304 20897 Married Female 30000 1 Bachelors
## 305 28207 Married Male 80000 4 Graduate Degree
## 306 25923 Single Male 10000 2 Partial High School
## 307 11000 Married Male 90000 2 Bachelors
## 308 20974 Married Male 10000 2 Bachelors
## 309 28758 Married Male 40000 2 Partial College
## 310 11381 Married Female 20000 2 Partial College
## 311 17522 Married Male 120000 4 Bachelors
## 312 21207 Married Male 60000 1 Partial College
## 313 28102 Married Male 20000 4 High School
## 314 23105 Single Male 40000 3 Partial High School
## 315 18740 Married Male 80000 5 Bachelors
## 316 21213 Single Male 70000 0 Bachelors
## 317 17352 Married Male 50000 2 Graduate Degree
## 318 14154 Married Male 30000 0 Bachelors
## 319 19066 Married Male 130000 4 Partial College
## 320 11386 Married Female 30000 3 Bachelors
## 321 20228 Married Male 100000 0 Graduate Degree
## 322 16675 Single Female 160000 0 Graduate Degree
## 323 16410 Single Female 10000 4 Partial High School
## 324 27760 Single Female 40000 0 Graduate Degree
## 325 22930 Married Male 90000 4 Bachelors
## 326 23780 Single Male 40000 2 Partial College
## 327 20994 Married Female 20000 0 Bachelors
## 328 28379 Married Male 30000 1 Bachelors
## 329 14865 Single Male 40000 2 Partial College
## 330 12663 Married Female 90000 5 Partial High School
## 331 24898 Single Female 80000 0 Bachelors
## 332 19508 Married Male 10000 0 Partial High School
## 333 11489 Single Female 20000 0 Partial High School
## 334 18160 Married Male 130000 3 High School
## 335 25241 Married Male 90000 2 Bachelors
## 336 24369 Married Female 80000 5 Graduate Degree
## 337 27165 Single Male 20000 0 Partial High School
## 338 29424 Married Male 10000 0 Partial High School
## 339 15926 Single Female 120000 3 High School
## 340 14554 Married Male 20000 1 Bachelors
## 341 16468 Single Male 30000 0 Partial College
## 342 19174 Single Female 30000 0 High School
## 343 19183 Single Male 10000 0 Partial High School
## 344 13683 Single Female 30000 0 High School
## 345 17848 Single Male 30000 0 Partial College
## 346 17894 Married Female 20000 1 Bachelors
## 347 25651 Married Male 40000 1 Bachelors
## 348 22936 Single Female 60000 1 Partial College
## 349 23915 Married Male 20000 2 High School
## 350 24121 Single Female 30000 0 Partial College
## 351 27878 Single Male 20000 0 Partial College
## 352 13572 Single Male 10000 3 High School
## 353 27941 Married Female 80000 4 Partial College
## 354 26354 Single Male 40000 0 Graduate Degree
## 355 14785 Single Male 30000 1 Bachelors
## 356 17238 Single Male 80000 0 Bachelors
## 357 23608 Married Female 150000 3 High School
## 358 22538 Single Female 10000 0 Partial High School
## 359 12332 Married Male 90000 4 High School
## 360 17230 Married Male 80000 0 Bachelors
## 361 13082 Single Male 130000 0 Graduate Degree
## 362 22518 Single Female 30000 3 Partial College
## 363 13687 Married Male 40000 1 Bachelors
## 364 23571 Married Female 40000 2 Bachelors
## 365 19305 Single Female 10000 2 High School
## 366 22636 Single Female 40000 0 Bachelors
## 367 17310 Married Male 60000 1 Partial College
## 368 12133 Married Female 130000 3 Partial College
## 369 25918 Single Female 30000 2 Partial College
## 370 25752 Single Female 20000 2 Partial College
## 371 17324 Married Female 100000 4 Bachelors
## 372 22918 Single Male 80000 5 Graduate Degree
## 373 12510 Married Male 40000 1 Bachelors
## 374 25512 Single Male 20000 0 High School
## 375 16179 Single Female 80000 5 Bachelors
## 376 15628 Married Female 40000 1 Bachelors
## 377 20977 Married Male 20000 1 Bachelors
## 378 18140 Married Male 130000 3 Partial College
## 379 20417 Married Male 30000 3 Partial College
## 380 18267 Married Male 60000 3 Bachelors
## 381 13620 Single Male 70000 0 Bachelors
## 382 22974 Married Female 30000 2 Partial College
## 383 13586 Married Male 80000 4 Partial College
## 384 17978 Married Male 40000 0 Graduate Degree
## 385 12581 Single Female 10000 0 Partial College
## 386 18018 Single Male 30000 3 Partial College
## 387 28957 Single Female 120000 3 Partial High School
## 388 13690 Single Female 20000 0 Partial High School
## 389 12568 Married Female 30000 1 Bachelors
## 390 13122 Married Female 80000 0 Bachelors
## 391 21184 Single Male 70000 0 Bachelors
## 392 26150 Single Female 70000 0 Bachelors
## 393 24151 Single Male 20000 1 Bachelors
## 394 23962 Married Female 10000 0 Partial High School
## 395 17793 Married Female 40000 0 Bachelors
## 396 14926 Married Male 30000 1 Bachelors
## 397 16163 Single Male 60000 2 Bachelors
## 398 21365 Married Female 10000 2 Partial High School
## 399 27771 Single Male 30000 1 Bachelors
## 400 26167 Single Female 40000 2 Bachelors
## 401 25792 Single Female 110000 3 Bachelors
## 402 11555 Married Female 40000 1 Bachelors
## 403 22381 Married Male 10000 1 Graduate Degree
## 404 17882 Married Male 20000 1 Graduate Degree
## 405 22174 Married Male 30000 3 High School
## 406 22439 Married Female 30000 0 Bachelors
## 407 18012 Married Female 40000 1 Bachelors
## 408 27582 Single Female 90000 2 Bachelors
## 409 12744 Single Female 40000 2 Partial College
## 410 22821 Married Female 130000 3 Partial College
## 411 20171 Married Female 20000 2 Partial College
## 412 11116 Married Male 70000 5 Partial College
## 413 20053 Single Male 40000 2 Partial College
## 414 25266 Single Female 30000 2 Partial College
## 415 17960 Married Female 40000 0 Graduate Degree
## 416 13961 Married Female 80000 5 Graduate Degree
## 417 11897 Single Male 60000 2 Bachelors
## 418 11139 Single Female 30000 2 Partial College
## 419 11576 Married Male 30000 1 Bachelors
## 420 19255 Single Male 10000 2 Partial College
## 421 18153 Married Female 100000 2 Bachelors
## 422 14547 Married Male 10000 2 Partial College
## 423 24901 Single Male 110000 0 Partial College
## 424 27169 Single Male 30000 0 High School
## 425 14805 Single Female 10000 3 Partial High School
## 426 15822 Married Male 40000 2 Bachelors
## 427 19389 Single Male 30000 0 Partial College
## 428 17048 Single Female 90000 1 Graduate Degree
## 429 22204 Married Male 110000 4 Bachelors
## 430 12718 Single Female 30000 0 Partial College
## 431 15019 Single Female 30000 3 High School
## 432 28488 Single Male 20000 0 Partial College
## 433 21891 Married Female 110000 0 High School
## 434 27814 Single Female 30000 3 Partial College
## 435 22175 Married Female 30000 3 High School
## 436 29447 Single Female 10000 2 Bachelors
## 437 19784 Married Female 80000 2 High School
## 438 27824 Single Female 30000 3 Partial College
## 439 24093 Single Female 80000 0 Graduate Degree
## 440 19618 Married Male 70000 5 Partial College
## 441 21561 Single Male 90000 0 Bachelors
## 442 11061 Married Male 60000 2 Partial College
## 443 26651 Single Male 80000 4 Graduate Degree
## 444 21108 Married Female 40000 1 Bachelors
## 445 12731 Single Male 30000 0 High School
## 446 25307 Married Female 40000 1 Bachelors
## 447 14278 Married Female 130000 0 Graduate Degree
## 448 20711 Married Female 40000 1 Bachelors
## 449 11383 Married Female 30000 3 Graduate Degree
## 450 12497 Married Female 40000 1 Bachelors
## 451 16559 Single Female 10000 2 High School
## 452 11585 Married Female 40000 1 Bachelors
## 453 20277 Married Female 30000 2 Partial College
## 454 26765 Single Female 70000 5 Partial College
## 455 12389 Single Male 30000 0 High School
## 456 13585 Married Female 80000 4 Partial College
## 457 26385 Single Male 120000 3 High School
## 458 12236 Married Female 20000 1 Partial College
## 459 21560 Married Male 120000 0 Partial High School
## 460 21554 Single Female 80000 0 Bachelors
## 461 13662 Single Male 20000 0 Partial High School
## 462 13089 Married Female 120000 1 Bachelors
## 463 14791 Married Female 40000 0 Bachelors
## 464 19331 Single Male 20000 2 High School
## 465 17754 Single Female 30000 3 Bachelors
## 466 11149 Married Male 40000 2 Bachelors
## 467 16549 Single Female 30000 3 Bachelors
## 468 24305 Single Male 100000 1 Bachelors
## 469 18253 Married Female 80000 5 Graduate Degree
## 470 20147 Married Female 30000 1 Bachelors
## 471 15612 Single Male 30000 0 High School
## 472 28323 Single Male 70000 0 Bachelors
## 473 22634 Single Female 40000 0 Graduate Degree
## 474 15665 Married Female 30000 0 Bachelors
## 475 27585 Married Female 90000 2 Bachelors
## 476 19748 Married Male 20000 4 High School
## 477 21974 Single Female 70000 0 Bachelors
## 478 14032 Married Male 70000 2 High School
## 479 22610 Married Male 30000 0 Bachelors
## 480 26984 Married Male 40000 1 Bachelors
## 481 18294 Married Female 90000 1 Bachelors
## 482 28564 Single Female 40000 2 Partial College
## 483 28521 Single Male 40000 0 Graduate Degree
## 484 15450 Married Male 10000 1 Graduate Degree
## 485 25681 Single Female 30000 0 Partial College
## 486 19491 Single Male 30000 2 Partial College
## 487 26415 Married Female 90000 4 Partial High School
## 488 12821 Married Male 40000 0 Bachelors
## 489 15629 Single Female 10000 0 Partial High School
## 490 27835 Married Male 20000 0 Partial High School
## 491 11738 Married Male 60000 4 Bachelors
## 492 25065 Married Male 70000 2 Partial High School
## 493 26238 Single Female 40000 3 Partial College
## 494 23707 Single Male 70000 5 Bachelors
## 495 27650 Married Male 70000 4 High School
## 496 24981 Married Male 60000 2 Partial College
## 497 20678 Single Female 60000 3 Bachelors
## 498 15302 Single Female 70000 1 Graduate Degree
## 499 26012 Married Male 80000 1 Partial College
## 500 26575 Single Female 40000 0 High School
## 501 15559 Married Male 60000 5 Bachelors
## 502 19235 Married Female 50000 0 Graduate Degree
## 503 15275 Married Male 40000 0 Partial College
## 504 20339 Married Female 130000 1 Bachelors
## 505 25405 Married Male 70000 2 Bachelors
## 506 15940 Married Male 100000 4 Partial College
## 507 25074 Married Female 70000 4 Bachelors
## 508 24738 Married Female 40000 1 Partial College
## 509 16337 Married Male 60000 0 Partial College
## 510 24357 Married Male 60000 3 Bachelors
## 511 18613 Single Male 70000 0 Bachelors
## 512 12207 Single Male 80000 4 Bachelors
## 513 18052 Married Female 60000 1 Partial College
## 514 13353 Single Female 60000 4 Graduate Degree
## 515 19399 Single Male 40000 0 Bachelors
## 516 16154 Married Female 70000 5 Bachelors
## 517 22219 Married Female 60000 2 High School
## 518 17269 Single Male 60000 3 Bachelors
## 519 23586 Married Female 80000 0 Bachelors
## 520 15740 Married Male 80000 5 Bachelors
## 521 27638 Single Male 100000 1 Partial College
## 522 18976 Single Male 40000 4 High School
## 523 19413 Single Male 60000 3 Bachelors
## 524 13283 Married Male 80000 3 Partial College
## 525 17471 Single Female 80000 4 Graduate Degree
## 526 16791 Single Male 60000 5 Bachelors
## 527 15382 Married Female 110000 1 Bachelors
## 528 11641 Married Male 50000 1 Bachelors
## 529 11935 Single Female 30000 0 Partial College
## 530 13233 Married Male 60000 2 Partial College
## 531 25909 Married Male 60000 0 Partial College
## 532 14092 Single Male 30000 0 Partial High School
## 533 29143 Single Female 60000 1 Bachelors
## 534 24941 Married Male 60000 3 Bachelors
## 535 24637 Married Male 40000 4 High School
## 536 23893 Married Male 50000 3 Bachelors
## 537 13907 Single Female 80000 3 Bachelors
## 538 14900 Married Female 40000 1 Partial College
## 539 11262 Married Female 80000 4 Bachelors
## 540 22294 Single Female 70000 0 Bachelors
## 541 12195 Single Female 70000 3 Graduate Degree
## 542 25375 Married Male 50000 1 Graduate Degree
## 543 11143 Married Male 40000 0 High School
## 544 25898 Married Female 70000 2 High School
## 545 24397 Single Male 120000 2 Bachelors
## 546 19758 Single Male 60000 0 Partial College
## 547 15529 Married Male 60000 4 Bachelors
## 548 19884 Married Male 60000 2 High School
## 549 18674 Single Female 80000 4 Graduate Degree
## 550 13453 Married Female 130000 1 Bachelors
## 551 14063 Single Female 70000 0 Bachelors
## 552 27393 Married Female 50000 4 Bachelors
## 553 14417 Single Male 60000 3 High School
## 554 17533 Married Male 40000 3 Partial College
## 555 18580 Married Female 60000 2 Graduate Degree
## 556 17025 Single Male 50000 0 Partial College
## 557 25293 Married Male 80000 4 Bachelors
## 558 24725 Married Female 40000 3 Partial College
## 559 23200 Married Female 50000 3 Bachelors
## 560 15895 Single Female 60000 2 Bachelors
## 561 18577 Married Female 60000 0 Graduate Degree
## 562 27218 Married Female 20000 2 Partial High School
## 563 18560 Married Female 70000 2 Graduate Degree
## 564 25006 Single Female 30000 0 Partial College
## 565 17369 Single Male 30000 0 Partial College
## 566 14495 Married Male 40000 3 Partial College
## 567 18847 Married Female 60000 2 Graduate Degree
## 568 14754 Married Male 40000 1 Partial College
## 569 23378 Married Male 70000 1 Partial College
## 570 26452 Single Male 50000 3 Graduate Degree
## 571 20370 Married Male 70000 3 Partial High School
## 572 20528 Married Male 40000 2 Partial High School
## 573 23549 Single Male 30000 0 High School
## 574 21751 Married Male 60000 3 Graduate Degree
## 575 21266 Single Female 80000 0 Bachelors
## 576 13388 Single Male 60000 2 Partial College
## 577 18752 Single Female 40000 0 High School
## 578 16917 Married Male 120000 1 Bachelors
## 579 15313 Married Male 60000 4 Bachelors
## 580 25329 Single Female 40000 3 Partial College
## 581 20380 Married Female 60000 3 Graduate Degree
## 582 23089 Married Male 40000 0 Partial College
## 583 13749 Married Male 80000 4 Graduate Degree
## 584 24943 Married Male 60000 3 Bachelors
## 585 28667 Single Male 70000 2 Bachelors
## 586 15194 Single Male 120000 2 Bachelors
## 587 17436 Married Male 60000 2 High School
## 588 18935 Married Female 130000 0 Graduate Degree
## 589 16871 Married Female 90000 2 High School
## 590 12100 Single Male 60000 2 Bachelors
## 591 23158 Married Female 60000 1 Graduate Degree
## 592 18545 Married Male 40000 4 High School
## 593 18391 Single Female 80000 5 Partial College
## 594 19812 Single Female 70000 2 Partial College
## 595 27660 Married Male 80000 4 Graduate Degree
## 596 18058 Single Female 20000 3 High School
## 597 20343 Married Female 90000 4 Partial College
## 598 28997 Single Male 40000 2 High School
## 599 24398 Married Male 130000 1 Graduate Degree
## 600 19002 Married Female 60000 2 Partial College
## 601 28609 Married Male 30000 2 High School
## 602 29231 Single Male 80000 4 Partial College
## 603 18858 Single Male 60000 2 Partial High School
## 604 20000 Married Male 60000 1 Graduate Degree
## 605 25261 Married Male 40000 0 High School
## 606 17458 Single Male 70000 3 High School
## 607 11644 Single Male 40000 2 Bachelors
## 608 16145 Single Female 70000 5 Graduate Degree
## 609 16890 Married Male 60000 3 Partial High School
## 610 25983 Married Male 70000 0 Bachelors
## 611 14633 Married Male 60000 1 Partial College
## 612 22994 Married Female 80000 0 Bachelors
## 613 22983 Single Female 30000 0 Partial High School
## 614 25184 Single Male 110000 1 Partial College
## 615 14469 Married Female 100000 3 Partial College
## 616 11538 Single Female 60000 4 Graduate Degree
## 617 16245 Single Female 80000 4 Graduate Degree
## 618 17858 Married Male 40000 4 High School
## 619 25347 Single Female 20000 3 Partial High School
## 620 15814 Single Female 40000 0 High School
## 621 11259 Married Female 100000 4 Partial College
## 622 11200 Married Male 70000 4 Bachelors
## 623 25101 Married Male 60000 5 Bachelors
## 624 21801 Married Female 70000 4 Partial College
## 625 25943 Single Female 70000 0 Partial College
## 626 22127 Married Male 60000 3 Graduate Degree
## 627 20414 Married Female 60000 0 Partial College
## 628 23672 Married Female 60000 3 Graduate Degree
## 629 29255 Single Male 80000 3 Partial College
## 630 28815 Married Female 50000 1 Graduate Degree
## 631 27753 Married Male 40000 0 High School
## 632 27643 Single Male 70000 5 Partial College
## 633 13754 Single Female 80000 4 Graduate Degree
## 634 22088 Married Female 130000 1 Bachelors
## 635 27388 Married Male 60000 3 Bachelors
## 636 24745 Single Female 30000 2 High School
## 637 29237 Single Female 120000 4 Partial College
## 638 15272 Single Male 40000 0 High School
## 639 18949 Single Male 70000 1 Graduate Degree
## 640 14507 Married Male 100000 2 Graduate Degree
## 641 25886 Married Female 60000 2 Partial College
## 642 21441 Married Male 50000 4 Bachelors
## 643 21741 Married Female 70000 3 Partial College
## 644 14572 Married Female 70000 3 Graduate Degree
## 645 23368 Married Female 60000 5 Bachelors
## 646 16217 Single Female 60000 0 Graduate Degree
## 647 16247 Single Female 60000 4 Graduate Degree
## 648 22010 Single Male 40000 0 High School
## 649 25872 Single Female 70000 2 Bachelors
## 650 19164 Single Female 70000 0 Bachelors
## 651 18435 Single Female 70000 5 Graduate Degree
## 652 14284 Single Male 60000 0 Partial College
## 653 11287 Married Male 70000 5 Partial College
## 654 13066 Single Male 30000 0 High School
## 655 29106 Single Male 40000 0 High School
## 656 26236 Married Female 40000 3 Partial College
## 657 17531 Married Male 60000 2 High School
## 658 12964 Married Male 70000 1 Partial College
## 659 19133 Single Male 50000 2 Bachelors
## 660 24643 Single Female 60000 4 Bachelors
## 661 21599 Married Female 60000 1 Graduate Degree
## 662 22976 Single Male 40000 0 High School
## 663 27637 Single Female 100000 1 Partial College
## 664 11890 Married Female 70000 5 Graduate Degree
## 665 28580 Married Female 80000 0 Graduate Degree
## 666 14443 Married Male 130000 1 Graduate Degree
## 667 17864 Married Female 60000 1 Partial College
## 668 20505 Married Female 40000 5 High School
## 669 14592 Married Female 60000 0 Graduate Degree
## 670 22227 Married Female 60000 2 High School
## 671 21471 Married Male 70000 2 Partial College
## 672 22252 Single Female 60000 1 Graduate Degree
## 673 21260 Single Female 40000 0 High School
## 674 11817 Single Female 70000 4 Graduate Degree
## 675 19223 Married Female 30000 2 High School
## 676 18517 Married Male 100000 3 Bachelors
## 677 21717 Married Male 40000 2 Partial College
## 678 13760 Married Male 60000 4 Graduate Degree
## 679 18145 Married Male 80000 5 Bachelors
## 680 21770 Married Male 60000 4 Bachelors
## 681 11165 Married Female 60000 0 Partial College
## 682 16377 Single Female 80000 4 Graduate Degree
## 683 26248 Married Male 20000 3 Partial High School
## 684 23461 Married Female 90000 5 Partial College
## 685 29133 Single Female 60000 4 Bachelors
## 686 27673 Single Female 60000 3 Graduate Degree
## 687 12774 Married Female 40000 1 Partial College
## 688 18910 Single Male 30000 0 Partial College
## 689 11699 Single Male 60000 3 Bachelors
## 690 16725 Married Male 30000 0 High School
## 691 28269 Single Female 130000 1 Bachelors
## 692 23144 Married Male 50000 1 Bachelors
## 693 23376 Married Male 70000 1 Bachelors
## 694 25970 Single Female 60000 4 Bachelors
## 695 28068 Single Female 80000 3 Graduate Degree
## 696 18390 Married Male 80000 5 Partial College
## 697 29112 Single Male 60000 0 Partial College
## 698 14090 Married Female 30000 0 Partial High School
## 699 27040 Married Male 20000 2 Partial High School
## 700 23479 Single Male 90000 0 Partial College
## 701 16795 Married Female 70000 4 Bachelors
## 702 22014 Single Male 30000 0 High School
## 703 13314 Married Male 120000 1 High School
## 704 11619 Single Female 50000 0 Graduate Degree
## 705 29132 Single Female 40000 0 Bachelors
## 706 11199 Married Female 70000 4 Bachelors
## 707 20296 Single Female 60000 0 Partial College
## 708 17546 Married Female 70000 1 Partial College
## 709 18069 Married Male 70000 5 Bachelors
## 710 23712 Single Female 70000 2 Bachelors
## 711 23358 Married Male 60000 0 High School
## 712 20518 Married Female 70000 2 Partial College
## 713 28026 Married Female 40000 2 High School
## 714 11669 Single Female 70000 2 Bachelors
## 715 16020 Married Male 40000 0 High School
## 716 27090 Married Female 60000 1 Graduate Degree
## 717 27198 Single Female 80000 0 Graduate Degree
## 718 19661 Single Male 90000 4 Bachelors
## 719 26327 Married Male 70000 4 Graduate Degree
## 720 26341 Married Female 70000 5 Graduate Degree
## 721 24958 Single Female 40000 5 High School
## 722 13287 Single Male 110000 4 Bachelors
## 723 14493 Single Female 70000 3 Graduate Degree
## 724 26678 Single Female 80000 2 Partial High School
## 725 23275 Married Male 30000 2 High School
## 726 11270 Married Male 130000 2 Graduate Degree
## 727 20084 Married Male 20000 2 High School
## 728 16144 Married Male 70000 1 Graduate Degree
## 729 27731 Married Male 40000 0 High School
## 730 11886 Married Female 60000 3 Bachelors
## 731 24324 Single Female 60000 4 Bachelors
## 732 22220 Married Male 60000 2 High School
## 733 26625 Single Female 60000 0 Graduate Degree
## 734 23027 Single Male 130000 1 Bachelors
## 735 16867 Single Female 130000 1 Bachelors
## 736 14514 Single Female 30000 0 Partial College
## 737 19634 Married Male 40000 0 High School
## 738 18504 Married Male 70000 2 Partial High School
## 739 28799 Single Female 40000 2 Partial College
## 740 11225 Married Female 60000 2 Partial College
## 741 17657 Married Male 40000 4 Partial College
## 742 14913 Married Female 40000 1 Partial College
## 743 14077 Single Male 30000 0 High School
## 744 13296 Married Male 110000 1 Bachelors
## 745 20535 Married Female 70000 4 Partial College
## 746 12452 Married Male 60000 4 Graduate Degree
## 747 28043 Married Female 60000 2 Bachelors
## 748 12957 Single Female 70000 1 Bachelors
## 749 15412 Married Male 130000 2 Graduate Degree
## 750 20514 Married Female 70000 2 Partial College
## 751 20758 Married Male 30000 2 High School
## 752 11801 Married Male 60000 1 Graduate Degree
## 753 22211 Married Male 60000 0 Partial College
## 754 28087 Single Female 40000 0 Partial College
## 755 23668 Married Female 40000 4 High School
## 756 27441 Married Male 60000 3 High School
## 757 27261 Married Male 40000 1 Bachelors
## 758 18649 Single Male 30000 1 High School
## 759 21714 Single Female 80000 5 Graduate Degree
## 760 23217 Single Female 60000 3 Graduate Degree
## 761 23797 Single Male 20000 3 Partial High School
## 762 13216 Married Female 60000 5 Bachelors
## 763 20657 Single Male 50000 2 Bachelors
## 764 12882 Married Male 50000 1 Graduate Degree
## 765 25908 Married Female 60000 0 Partial College
## 766 16753 Single Female 70000 0 Partial College
## 767 14608 Married Male 50000 4 Bachelors
## 768 24979 Married Female 60000 2 Partial College
## 769 13313 Married Female 120000 1 High School
## 770 18952 Married Female 100000 4 Bachelors
## 771 17699 Married Male 60000 1 Graduate Degree
## 772 14657 Married Male 80000 1 Partial College
## 773 11540 Single Male 60000 4 Graduate Degree
## 774 11783 Married Female 60000 1 Graduate Degree
## 775 14602 Married Female 80000 3 Graduate Degree
## 776 29030 Married Male 70000 2 Partial High School
## 777 26490 Single Male 70000 2 Bachelors
## 778 13151 Single Male 40000 0 High School
## 779 17260 Married Male 90000 5 Partial College
## 780 15372 Married Male 80000 3 Partial College
## 781 18105 Married Female 60000 2 Partial College
## 782 19660 Married Male 80000 4 Bachelors
## 783 16112 Single Male 70000 4 Bachelors
## 784 20698 Married Male 60000 4 Bachelors
## 785 20076 Single Female 10000 2 High School
## 786 24496 Single Female 40000 0 High School
## 787 15468 Married Female 50000 1 Bachelors
## 788 28031 Single Female 70000 2 Bachelors
## 789 26270 Single Female 20000 2 Partial High School
## 790 22221 Married Male 60000 2 High School
## 791 28228 Single Female 80000 2 Partial High School
## 792 18363 Married Male 40000 0 High School
## 793 23256 Single Male 30000 1 High School
## 794 12768 Married Male 30000 1 High School
## 795 20361 Married Male 50000 2 Graduate Degree
## 796 21306 Single Male 60000 2 High School
## 797 13382 Married Male 70000 5 Partial College
## 798 20310 Single Male 60000 0 Partial College
## 799 22971 Single Female 30000 0 High School
## 800 15287 Single Female 50000 1 Graduate Degree
## 801 15532 Single Male 60000 4 Bachelors
## 802 11255 Married Male 70000 4 Graduate Degree
## 803 28090 Married Male 40000 0 Partial College
## 804 15255 Married Male 40000 0 High School
## 805 13154 Married Male 40000 0 High School
## 806 26778 Single Female 40000 3 High School
## 807 23248 Married Female 10000 2 High School
## 808 21417 Single Female 60000 0 Partial College
## 809 17668 Single Male 30000 2 High School
## 810 27994 Married Female 40000 4 High School
## 811 20376 Single Female 70000 3 Graduate Degree
## 812 25954 Married Male 60000 0 Partial College
## 813 15749 Single Female 70000 4 Bachelors
## 814 25899 Married Female 70000 2 High School
## 815 13351 Single Female 70000 4 Bachelors
## 816 23333 Married Male 40000 0 Partial College
## 817 21660 Married Female 60000 3 Graduate Degree
## 818 17012 Married Female 60000 3 Graduate Degree
## 819 24514 Married Male 40000 0 Partial College
## 820 27505 Single Female 40000 0 High School
## 821 29243 Single Male 110000 1 Bachelors
## 822 26582 Married Male 60000 0 Partial College
## 823 14271 Married Male 30000 0 High School
## 824 23041 Single Female 70000 4 High School
## 825 29048 Single Male 110000 2 Bachelors
## 826 24433 Married Male 70000 3 High School
## 827 15501 Married Male 70000 4 Graduate Degree
## 828 13911 Single Female 80000 3 Bachelors
## 829 20421 Single Female 40000 0 Partial High School
## 830 16009 Single Male 170000 1 Graduate Degree
## 831 18411 Married Male 60000 2 High School
## 832 19163 Married Female 70000 4 Bachelors
## 833 18572 Married Female 60000 0 Graduate Degree
## 834 27540 Single Female 70000 0 Bachelors
## 835 19889 Single Female 70000 2 Partial High School
## 836 12922 Single Female 60000 3 Bachelors
## 837 18891 Married Female 40000 0 Partial College
## 838 16773 Married Male 60000 1 Graduate Degree
## 839 19143 Single Female 80000 3 Bachelors
## 840 23882 Single Female 80000 3 Graduate Degree
## 841 11233 Married Male 70000 4 Partial College
## 842 12056 Married Male 120000 2 Graduate Degree
## 843 15555 Married Female 60000 1 Partial College
## 844 18423 Single Male 80000 2 Partial High School
## 845 22743 Married Female 40000 5 High School
## 846 25343 Single Female 20000 3 Partial High School
## 847 13390 Married Female 70000 4 Partial College
## 848 17482 Single Female 40000 0 Partial High School
## 849 13176 Single Male 130000 0 Graduate Degree
## 850 20504 Married Female 40000 5 High School
## 851 12205 Single Female 130000 2 Bachelors
## 852 16751 Married Male 60000 0 Partial College
## 853 21613 Single Male 50000 2 Bachelors
## 854 24801 Single Male 60000 1 Graduate Degree
## 855 17519 Married Female 60000 0 Partial College
## 856 18347 Single Female 30000 0 Partial College
## 857 29052 Single Male 40000 0 Partial College
## 858 11745 Married Female 60000 1 Bachelors
## 859 19147 Married Male 40000 0 Bachelors
## 860 19217 Married Male 30000 2 High School
## 861 15839 Single Male 30000 0 Partial College
## 862 13714 Married Female 20000 2 High School
## 863 22330 Married Male 50000 0 Graduate Degree
## 864 18783 Single Male 80000 0 Bachelors
## 865 25041 Single Male 40000 0 High School
## 866 22046 Single Female 80000 0 Bachelors
## 867 28052 Married Male 60000 2 High School
## 868 26693 Married Male 70000 3 Partial College
## 869 24955 Single Male 30000 5 Partial High School
## 870 26065 Single Female 110000 3 Bachelors
## 871 13942 Married Male 60000 1 Partial College
## 872 11219 Married Male 60000 2 High School
## 873 22118 Single Female 70000 3 Graduate Degree
## 874 23197 Married Male 50000 3 Bachelors
## 875 14883 Married Female 30000 1 Bachelors
## 876 27279 Single Female 70000 2 Bachelors
## 877 18322 Single Male 30000 0 Partial High School
## 878 15879 Married Male 70000 5 Bachelors
## 879 28278 Married Male 50000 2 Graduate Degree
## 880 24416 Married Male 90000 4 High School
## 881 28066 Married Male 80000 2 Graduate Degree
## 882 11275 Married Female 80000 4 Graduate Degree
## 883 14872 Married Male 30000 0 Graduate Degree
## 884 16151 Married Female 60000 1 Bachelors
## 885 19731 Married Male 80000 4 Graduate Degree
## 886 23801 Married Female 20000 2 Partial High School
## 887 11807 Married Male 70000 3 Graduate Degree
## 888 11622 Married Male 50000 0 Graduate Degree
## 889 26597 Single Female 60000 4 Bachelors
## 890 27074 Married Female 70000 1 Graduate Degree
## 891 19228 Married Female 40000 2 Partial College
## 892 13415 Single Male 100000 1 Graduate Degree
## 893 17000 Single Female 70000 4 Bachelors
## 894 14569 Married Male 60000 1 Graduate Degree
## 895 13873 Married Male 70000 3 Graduate Degree
## 896 20401 Married Female 50000 4 Bachelors
## 897 21583 Married Female 50000 1 Bachelors
## 898 12029 Married Male 30000 0 Partial High School
## 899 18066 Single Male 70000 5 Bachelors
## 900 28192 Married Female 70000 5 Graduate Degree
## 901 16122 Married Male 40000 4 High School
## 902 18607 Single Female 60000 4 Bachelors
## 903 28858 Single Male 80000 3 Bachelors
## 904 14432 Single Male 90000 4 Graduate Degree
## 905 26305 Single Female 60000 2 Bachelors
## 906 22050 Single Male 90000 4 Bachelors
## 907 25394 Married Male 60000 1 Graduate Degree
## 908 19747 Married Male 50000 4 Bachelors
## 909 23195 Single Female 50000 3 Bachelors
## 910 21695 Married Male 60000 0 Graduate Degree
## 911 13934 Married Male 40000 4 High School
## 912 13337 Married Female 80000 5 Bachelors
## 913 27190 Married Female 40000 3 Partial College
## 914 28657 Single Male 60000 2 Bachelors
## 915 21713 Single Male 80000 5 Graduate Degree
## 916 21752 Married Male 60000 3 Graduate Degree
## 917 27273 Single Male 70000 3 Graduate Degree
## 918 22719 Single Male 110000 3 Bachelors
## 919 22042 Married Female 70000 0 Partial College
## 920 21451 Married Female 40000 4 High School
## 921 20754 Married Male 30000 2 High School
## 922 12153 Single Female 70000 3 Partial College
## 923 16895 Married Female 40000 3 Partial College
## 924 26728 Single Male 70000 3 Graduate Degree
## 925 11090 Single Male 90000 2 Partial College
## 926 15862 Single Female 50000 0 Graduate Degree
## 927 26495 Single Female 40000 2 High School
## 928 11823 Married Female 70000 0 Graduate Degree
## 929 23449 Married Male 60000 2 High School
## 930 23459 Married Male 60000 2 High School
## 931 19543 Married Male 70000 5 Graduate Degree
## 932 14914 Married Female 40000 1 Partial College
## 933 12033 Single Female 40000 0 High School
## 934 11941 Single Male 60000 0 Partial College
## 935 14389 Married Male 60000 2 Bachelors
## 936 18050 Married Female 60000 1 Partial College
## 937 19856 Married Female 60000 4 Bachelors
## 938 11663 Married Male 70000 4 Graduate Degree
## 939 27740 Married Female 40000 0 High School
## 940 23455 Single Male 80000 2 Partial High School
## 941 15292 Single Female 60000 1 Graduate Degree
## 942 21587 Married Female 60000 1 Graduate Degree
## 943 23513 Married Female 40000 3 Partial College
## 944 24322 Married Female 60000 4 Bachelors
## 945 26298 Married Female 50000 1 Bachelors
## 946 25419 Single Male 50000 2 Bachelors
## 947 13343 Married Female 90000 5 Bachelors
## 948 11303 Single Female 90000 4 High School
## 949 21693 Single Female 60000 0 Graduate Degree
## 950 28056 Married Male 70000 2 Partial High School
## 951 11788 Single Female 70000 1 Graduate Degree
## 952 22296 Married Male 70000 0 Bachelors
## 953 15319 Married Female 70000 4 Bachelors
## 954 17654 Single Female 40000 3 Partial College
## 955 14662 Married Male 60000 1 Bachelors
## 956 17541 Married Female 40000 4 High School
## 957 13886 Married Female 70000 4 Graduate Degree
## 958 13073 Married Female 60000 0 Partial College
## 959 21940 Married Male 90000 5 Graduate Degree
## 960 20196 Married Male 60000 1 Partial College
## 961 23491 Single Male 100000 0 Partial College
## 962 16651 Married Female 120000 2 Bachelors
## 963 16813 Married Male 60000 2 Partial College
## 964 16007 Married Female 90000 5 Bachelors
## 965 27434 Single Male 70000 4 Partial College
## 966 27756 Single Female 50000 3 Bachelors
## 967 23818 Married Female 50000 0 Graduate Degree
## 968 19012 Married Male 80000 3 Bachelors
## 969 18329 Single Male 30000 0 Partial High School
## 970 29037 Married Male 60000 0 Graduate Degree
## 971 26576 Married Female 60000 0 Partial College
## 972 12192 Single Female 60000 2 Partial High School
## 973 14887 Married Female 30000 1 High School
## 974 11734 Married Female 60000 1 Partial College
## 975 17462 Married Male 70000 3 Graduate Degree
## 976 20659 Married Male 70000 3 Graduate Degree
## 977 28004 Married Female 60000 3 Bachelors
## 978 19741 Single Female 80000 4 Graduate Degree
## 979 17450 Married Male 80000 5 Partial College
## 980 17337 Single Male 40000 0 High School
## 981 18594 Single Female 80000 3 Bachelors
## 982 15982 Married Male 110000 5 Partial College
## 983 28625 Single Male 40000 2 Partial College
## 984 11269 Married Male 130000 2 Graduate Degree
## 985 25148 Married Male 60000 2 High School
## 986 13920 Single Female 50000 4 Bachelors
## 987 23704 Single Male 40000 5 High School
## 988 28972 Single Female 60000 3 Graduate Degree
## 989 22730 Married Male 70000 5 Bachelors
## 990 29134 Married Male 60000 4 Bachelors
## 991 14332 Single Female 30000 0 High School
## 992 19117 Single Female 60000 1 Graduate Degree
## 993 22864 Married Male 90000 2 Partial College
## 994 11292 Single Male 150000 1 Partial College
## 995 13466 Married Male 80000 5 Partial College
## 996 23731 Married Male 60000 2 High School
## 997 28672 Single Male 70000 4 Graduate Degree
## 998 11809 Married Male 60000 2 Bachelors
## 999 19664 Single Male 100000 3 Bachelors
## 1000 12121 Single Male 60000 3 High School
## occupation home_owner cars commute_distance region age
## 1 Skilled Manual Yes 0 0-1 Miles Europe 42
## 2 Clerical Yes 1 0-1 Miles Europe 43
## 3 Professional No 2 2-5 Miles Europe 60
## 4 Professional Yes 1 5-10 Miles Pacific 41
## 5 Clerical No 0 0-1 Miles Europe 36
## 6 Manual Yes 0 1-2 Miles Europe 50
## 7 Management Yes 4 0-1 Miles Pacific 33
## 8 Skilled Manual Yes 0 0-1 Miles Europe 43
## 9 Clerical Yes 2 5-10 Miles Pacific 58
## 10 Manual Yes 1 0-1 Miles Europe 27
## 11 Skilled Manual No 2 1-2 Miles Pacific 54
## 12 Professional No 4 10+ Miles Pacific 36
## 13 Professional Yes 2 0-1 Miles Europe 55
## 14 Clerical Yes 1 1-2 Miles Europe 35
## 15 Skilled Manual No 1 0-1 Miles Pacific 45
## 16 Manual Yes 1 0-1 Miles Europe 38
## 17 Clerical No 2 1-2 Miles Pacific 59
## 18 Clerical Yes 0 0-1 Miles Europe 47
## 19 Clerical Yes 1 1-2 Miles Europe 35
## 20 Clerical Yes 2 5-10 Miles Pacific 55
## 21 Clerical Yes 0 0-1 Miles Europe 36
## 22 Professional Yes 4 10+ Miles Pacific 35
## 23 Clerical Yes 0 1-2 Miles Europe 35
## 24 Management No 3 5-10 Miles Europe 56
## 25 Clerical No 1 0-1 Miles Europe 34
## 26 Clerical Yes 0 0-1 Miles Europe 63
## 27 Clerical No 1 0-1 Miles Europe 29
## 28 Professional No 1 5-10 Miles Pacific 40
## 29 Skilled Manual Yes 2 5-10 Miles Pacific 44
## 30 Manual No 2 0-1 Miles Europe 32
## 31 Manual Yes 0 0-1 Miles Europe 63
## 32 Manual No 1 0-1 Miles Pacific 26
## 33 Manual No 1 5-10 Miles Europe 31
## 34 Skilled Manual No 2 1-2 Miles Pacific 50
## 35 Professional No 2 2-5 Miles Europe 62
## 36 Manual No 2 0-1 Miles Europe 41
## 37 Manual Yes 1 0-1 Miles Europe 50
## 38 Clerical No 1 2-5 Miles Europe 30
## 39 Manual No 1 2-5 Miles Europe 28
## 40 Manual Yes 2 0-1 Miles Europe 40
## 41 Clerical No 0 0-1 Miles Europe 43
## 42 Management Yes 2 5-10 Miles Pacific 65
## 43 Manual Yes 0 0-1 Miles Europe 40
## 44 Professional No 3 5-10 Miles Europe 48
## 45 Manual Yes 0 0-1 Miles Europe 41
## 46 Clerical Yes 0 0-1 Miles Europe 66
## 47 Skilled Manual Yes 1 5-10 Miles Pacific 46
## 48 Skilled Manual Yes 2 5-10 Miles Pacific 52
## 49 Clerical No 2 0-1 Miles Europe 42
## 50 Clerical Yes 0 0-1 Miles Europe 39
## 51 Clerical No 1 0-1 Miles Europe 28
## 52 Professional No 4 10+ Miles Pacific 35
## 53 Clerical Yes 0 0-1 Miles Europe 65
## 54 Management No 3 5-10 Miles Europe 56
## 55 Professional No 1 5-10 Miles Pacific 42
## 56 Professional Yes 2 10+ Miles Europe 54
## 57 Clerical Yes 0 0-1 Miles Europe 38
## 58 Professional No 4 5-10 Miles Europe 61
## 59 Skilled Manual Yes 0 0-1 Miles Europe 43
## 60 Professional Yes 1 2-5 Miles Pacific 38
## 61 Manual No 1 1-2 Miles Europe 45
## 62 Manual Yes 0 0-1 Miles Europe 35
## 63 Management Yes 1 0-1 Miles Pacific 52
## 64 Professional Yes 3 10+ Miles Pacific 41
## 65 Clerical Yes 0 0-1 Miles Europe 37
## 66 Clerical Yes 2 5-10 Miles Pacific 68
## 67 Clerical Yes 0 0-1 Miles Europe 37
## 68 Manual Yes 1 2-5 Miles Europe 33
## 69 Manual Yes 1 0-1 Miles Europe 43
## 70 Manual No 2 0-1 Miles Europe 30
## 71 Professional Yes 4 10+ Miles Pacific 36
## 72 Manual No 2 0-1 Miles Europe 35
## 73 Professional Yes 4 0-1 Miles Europe 52
## 74 Manual No 1 2-5 Miles Europe 36
## 75 Skilled Manual No 2 1-2 Miles Pacific 62
## 76 Management Yes 4 0-1 Miles Pacific 31
## 77 Manual No 2 1-2 Miles Europe 26
## 78 Professional Yes 2 10+ Miles Pacific 29
## 79 Skilled Manual No 2 1-2 Miles Pacific 50
## 80 Management Yes 2 5-10 Miles Pacific 63
## 81 Clerical Yes 0 0-1 Miles Europe 45
## 82 Manual Yes 2 0-1 Miles Europe 40
## 83 Clerical Yes 0 0-1 Miles Europe 47
## 84 Manual No 1 2-5 Miles Europe 29
## 85 Management No 1 5-10 Miles Pacific 52
## 86 Manual Yes 1 1-2 Miles Pacific 26
## 87 Professional No 3 0-1 Miles Europe 51
## 88 Professional Yes 4 1-2 Miles Pacific 40
## 89 Clerical No 1 2-5 Miles Europe 29
## 90 Manual No 1 1-2 Miles Europe 40
## 91 Clerical No 1 0-1 Miles Europe 29
## 92 Clerical No 1 0-1 Miles Europe 30
## 93 Professional Yes 1 2-5 Miles Pacific 37
## 94 Clerical No 1 2-5 Miles Europe 33
## 95 Skilled Manual Yes 2 5-10 Miles Pacific 55
## 96 Professional Yes 2 10+ Miles Europe 62
## 97 Clerical Yes 1 0-1 Miles Europe 43
## 98 Skilled Manual Yes 1 0-1 Miles Europe 44
## 99 Clerical Yes 0 0-1 Miles Europe 44
## 100 Manual Yes 2 0-1 Miles Europe 43
## 101 Manual Yes 0 0-1 Miles Europe 35
## 102 Professional No 2 0-1 Miles Pacific 43
## 103 Manual Yes 0 1-2 Miles Europe 49
## 104 Skilled Manual Yes 1 5-10 Miles Pacific 45
## 105 Professional Yes 2 5-10 Miles Pacific 49
## 106 Clerical No 1 2-5 Miles Europe 30
## 107 Skilled Manual Yes 2 5-10 Miles Pacific 52
## 108 Skilled Manual No 2 1-2 Miles Pacific 53
## 109 Clerical Yes 0 0-1 Miles Europe 38
## 110 Professional No 0 0-1 Miles Europe 39
## 111 Manual No 0 0-1 Miles Europe 46
## 112 Professional No 1 5-10 Miles Pacific 38
## 113 Clerical Yes 2 1-2 Miles Europe 35
## 114 Management No 1 0-1 Miles Pacific 36
## 115 Clerical Yes 0 0-1 Miles Pacific 26
## 116 Manual No 0 0-1 Miles Europe 30
## 117 Skilled Manual Yes 2 0-1 Miles Europe 42
## 118 Manual Yes 0 0-1 Miles Europe 40
## 119 Management Yes 2 2-5 Miles Europe 62
## 120 Clerical No 1 2-5 Miles Europe 29
## 121 Management Yes 2 5-10 Miles Pacific 66
## 122 Professional Yes 4 0-1 Miles Europe 48
## 123 Professional No 3 10+ Miles Pacific 31
## 124 Management No 4 5-10 Miles Europe 56
## 125 Clerical No 0 0-1 Miles Europe 38
## 126 Professional Yes 4 1-2 Miles Pacific 40
## 127 Clerical Yes 1 2-5 Miles Europe 32
## 128 Clerical Yes 1 2-5 Miles Europe 39
## 129 Manual Yes 1 0-1 Miles Europe 52
## 130 Manual Yes 1 0-1 Miles Europe 39
## 131 Professional Yes 1 2-5 Miles Pacific 37
## 132 Management Yes 3 5-10 Miles Europe 56
## 133 Professional Yes 0 0-1 Miles Europe 40
## 134 Management Yes 2 5-10 Miles Pacific 65
## 135 Clerical Yes 2 0-1 Miles Europe 42
## 136 Manual Yes 1 2-5 Miles Europe 52
## 137 Manual No 1 5-10 Miles Europe 35
## 138 Manual Yes 2 0-1 Miles Europe 42
## 139 Clerical Yes 2 5-10 Miles Pacific 55
## 140 Clerical No 2 5-10 Miles Pacific 60
## 141 Professional No 0 0-1 Miles Europe 40
## 142 Manual No 1 0-1 Miles Pacific 26
## 143 Skilled Manual Yes 0 0-1 Miles Europe 42
## 144 Professional Yes 3 10+ Miles Pacific 32
## 145 Clerical Yes 0 1-2 Miles Europe 37
## 146 Clerical No 1 0-1 Miles Europe 34
## 147 Clerical Yes 0 0-1 Miles Europe 37
## 148 Professional No 0 0-1 Miles Europe 40
## 149 Skilled Manual Yes 2 5-10 Miles Pacific 60
## 150 Clerical No 1 1-2 Miles Europe 27
## 151 Skilled Manual Yes 1 5-10 Miles Pacific 43
## 152 Management No 3 0-1 Miles Pacific 48
## 153 Manual No 2 1-2 Miles Europe 32
## 154 Management Yes 3 2-5 Miles Pacific 47
## 155 Management Yes 3 0-1 Miles Pacific 40
## 156 Manual Yes 2 0-1 Miles Europe 41
## 157 Professional Yes 4 0-1 Miles Europe 59
## 158 Manual No 0 0-1 Miles Europe 50
## 159 Manual No 1 0-1 Miles Europe 54
## 160 Manual Yes 0 0-1 Miles Europe 48
## 161 Professional Yes 1 5-10 Miles Pacific 44
## 162 Manual Yes 0 0-1 Miles Europe 40
## 163 Professional No 1 0-1 Miles Pacific 38
## 164 Skilled Manual No 2 1-2 Miles Pacific 52
## 165 Manual Yes 1 2-5 Miles Pacific 25
## 166 Manual No 1 0-1 Miles Pacific 25
## 167 Professional Yes 1 2-5 Miles Pacific 47
## 168 Management Yes 3 10+ Miles Pacific 35
## 169 Professional No 1 5-10 Miles Pacific 41
## 170 Clerical Yes 0 0-1 Miles Europe 47
## 171 Professional Yes 4 5-10 Miles Europe 61
## 172 Management Yes 2 2-5 Miles Europe 61
## 173 Manual No 2 0-1 Miles Europe 33
## 174 Manual Yes 1 2-5 Miles Pacific 27
## 175 Skilled Manual Yes 0 0-1 Miles Europe 37
## 176 Skilled Manual Yes 2 5-10 Miles Pacific 52
## 177 Manual Yes 0 0-1 Miles Pacific 29
## 178 Professional No 3 5-10 Miles Europe 48
## 179 Professional No 2 10+ Miles Europe 55
## 180 Manual Yes 0 0-1 Miles Europe 37
## 181 Manual Yes 0 0-1 Miles Europe 44
## 182 Clerical No 2 1-2 Miles Pacific 55
## 183 Manual No 1 0-1 Miles Europe 38
## 184 Management Yes 2 5-10 Miles Pacific 66
## 185 Management No 4 10+ Miles Europe 58
## 186 Professional Yes 1 2-5 Miles Pacific 47
## 187 Skilled Manual No 2 1-2 Miles Pacific 56
## 188 Professional No 2 10+ Miles Europe 59
## 189 Professional Yes 4 10+ Miles Pacific 32
## 190 Clerical Yes 1 0-1 Miles Europe 44
## 191 Skilled Manual Yes 2 5-10 Miles Pacific 55
## 192 Manual Yes 0 0-1 Miles Europe 36
## 193 Management Yes 2 10+ Miles Europe 62
## 194 Professional Yes 4 10+ Miles Pacific 41
## 195 Manual No 2 0-1 Miles Europe 32
## 196 Clerical Yes 0 0-1 Miles Pacific 25
## 197 Skilled Manual Yes 1 1-2 Miles Europe 36
## 198 Management Yes 1 0-1 Miles Pacific 67
## 199 Management No 1 1-2 Miles Pacific 39
## 200 Professional No 3 10+ Miles Pacific 33
## 201 Professional No 3 2-5 Miles Pacific 31
## 202 Manual Yes 0 2-5 Miles Pacific 27
## 203 Clerical Yes 0 1-2 Miles Europe 33
## 204 Skilled Manual Yes 1 5-10 Miles Pacific 46
## 205 Professional No 1 2-5 Miles Europe 51
## 206 Clerical Yes 0 0-1 Miles Europe 46
## 207 Professional No 2 10+ Miles Europe 62
## 208 Manual Yes 2 1-2 Miles Europe 26
## 209 Clerical Yes 0 0-1 Miles Europe 37
## 210 Clerical Yes 0 0-1 Miles Europe 42
## 211 Management Yes 1 0-1 Miles Pacific 36
## 212 Skilled Manual Yes 0 0-1 Miles Europe 36
## 213 Clerical No 1 2-5 Miles Europe 30
## 214 Professional No 4 10+ Miles Pacific 31
## 215 Clerical Yes 0 0-1 Miles Europe 65
## 216 Professional No 2 2-5 Miles Europe 54
## 217 Clerical Yes 3 5-10 Miles Pacific 54
## 218 Manual No 2 0-1 Miles Europe 25
## 219 Manual Yes 0 0-1 Miles Europe 48
## 220 Manual Yes 1 1-2 Miles Pacific 26
## 221 Professional Yes 1 5-10 Miles Pacific 43
## 222 Manual No 2 1-2 Miles Europe 35
## 223 Clerical No 0 0-1 Miles Europe 42
## 224 Professional Yes 4 10+ Miles Pacific 39
## 225 Clerical No 2 0-1 Miles Pacific 67
## 226 Manual Yes 0 1-2 Miles Europe 38
## 227 Manual Yes 1 0-1 Miles Europe 42
## 228 Manual Yes 2 0-1 Miles Europe 43
## 229 Clerical Yes 0 0-1 Miles Europe 45
## 230 Management Yes 3 10+ Miles Europe 57
## 231 Management Yes 3 10+ Miles Europe 56
## 232 Clerical Yes 0 0-1 Miles Europe 38
## 233 Clerical Yes 0 0-1 Miles Europe 45
## 234 Clerical Yes 0 0-1 Miles Pacific 27
## 235 Professional No 4 10+ Miles Pacific 35
## 236 Clerical Yes 0 0-1 Miles Europe 70
## 237 Clerical Yes 0 0-1 Miles Europe 44
## 238 Manual No 1 0-1 Miles Pacific 26
## 239 Skilled Manual Yes 3 5-10 Miles Pacific 46
## 240 Manual No 1 2-5 Miles Europe 34
## 241 Manual Yes 0 0-1 Miles Europe 37
## 242 Clerical Yes 2 0-1 Miles Europe 27
## 243 Clerical No 1 0-1 Miles Europe 39
## 244 Manual No 1 2-5 Miles Europe 29
## 245 Management No 2 10+ Miles Europe 52
## 246 Management Yes 4 2-5 Miles Pacific 48
## 247 Professional Yes 3 0-1 Miles Europe 51
## 248 Management Yes 4 10+ Miles Pacific 34
## 249 Skilled Manual No 3 1-2 Miles Pacific 62
## 250 Professional Yes 1 5-10 Miles Pacific 37
## 251 Management No 1 1-2 Miles Pacific 78
## 252 Professional Yes 3 0-1 Miles Europe 55
## 253 Professional No 4 2-5 Miles Pacific 31
## 254 Professional Yes 0 10+ Miles Europe 59
## 255 Clerical Yes 2 5-10 Miles Pacific 57
## 256 Clerical Yes 0 0-1 Miles Europe 47
## 257 Clerical Yes 0 0-1 Miles Europe 43
## 258 Skilled Manual Yes 0 0-1 Miles Europe 36
## 259 Management Yes 4 10+ Miles Europe 56
## 260 Management Yes 4 0-1 Miles Pacific 37
## 261 Clerical Yes 0 0-1 Miles Europe 43
## 262 Skilled Manual Yes 1 1-2 Miles Europe 33
## 263 Manual Yes 0 1-2 Miles Europe 51
## 264 Professional Yes 3 10+ Miles Pacific 39
## 265 Clerical Yes 0 0-1 Miles Europe 37
## 266 Clerical Yes 2 0-1 Miles Europe 42
## 267 Manual Yes 2 0-1 Miles Europe 27
## 268 Professional Yes 1 5-10 Miles Pacific 47
## 269 Skilled Manual Yes 3 5-10 Miles Pacific 45
## 270 Skilled Manual No 0 0-1 Miles Europe 37
## 271 Manual Yes 0 0-1 Miles Europe 51
## 272 Manual No 1 1-2 Miles Europe 28
## 273 Manual Yes 1 0-1 Miles Europe 40
## 274 Manual No 1 2-5 Miles Europe 30
## 275 Clerical No 0 0-1 Miles Europe 36
## 276 Management Yes 0 0-1 Miles Pacific 37
## 277 Manual Yes 0 1-2 Miles Europe 49
## 278 Manual Yes 0 0-1 Miles Europe 37
## 279 Management Yes 3 10+ Miles Pacific 35
## 280 Clerical No 0 0-1 Miles Europe 38
## 281 Manual Yes 2 0-1 Miles Europe 43
## 282 Manual No 0 0-1 Miles Europe 37
## 283 Manual No 2 0-1 Miles Europe 34
## 284 Skilled Manual No 3 5-10 Miles Pacific 46
## 285 Manual Yes 0 0-1 Miles Europe 49
## 286 Skilled Manual Yes 1 5-10 Miles Pacific 45
## 287 Management Yes 4 2-5 Miles Pacific 48
## 288 Clerical No 0 0-1 Miles Europe 46
## 289 Management Yes 0 5-10 Miles Pacific 48
## 290 Skilled Manual Yes 2 5-10 Miles Pacific 54
## 291 Skilled Manual No 1 0-1 Miles Pacific 46
## 292 Clerical No 0 0-1 Miles Europe 38
## 293 Skilled Manual Yes 0 0-1 Miles Europe 42
## 294 Manual No 1 2-5 Miles Europe 46
## 295 Manual No 1 2-5 Miles Europe 36
## 296 Management Yes 3 10+ Miles Pacific 32
## 297 Professional No 1 0-1 Miles Pacific 39
## 298 Management Yes 0 2-5 Miles Pacific 36
## 299 Professional No 2 2-5 Miles Europe 54
## 300 Clerical No 2 5-10 Miles Pacific 69
## 301 Skilled Manual No 2 1-2 Miles Pacific 62
## 302 Clerical No 0 0-1 Miles Pacific 28
## 303 Clerical Yes 0 0-1 Miles Europe 62
## 304 Skilled Manual Yes 2 0-1 Miles Europe 40
## 305 Management Yes 1 0-1 Miles Pacific 36
## 306 Clerical Yes 2 5-10 Miles Pacific 58
## 307 Professional Yes 0 1-2 Miles Pacific 40
## 308 Clerical Yes 1 0-1 Miles Europe 66
## 309 Clerical Yes 1 1-2 Miles Europe 35
## 310 Manual Yes 1 2-5 Miles Europe 47
## 311 Management Yes 1 2-5 Miles Pacific 47
## 312 Skilled Manual Yes 1 5-10 Miles Pacific 46
## 313 Skilled Manual Yes 2 5-10 Miles Pacific 58
## 314 Clerical No 2 5-10 Miles Pacific 52
## 315 Professional No 1 0-1 Miles Pacific 47
## 316 Professional No 1 5-10 Miles Pacific 41
## 317 Management Yes 1 5-10 Miles Pacific 64
## 318 Clerical Yes 0 0-1 Miles Europe 35
## 319 Professional No 3 10+ Miles Europe 54
## 320 Clerical Yes 0 0-1 Miles Europe 45
## 321 Management Yes 0 2-5 Miles Pacific 40
## 322 Management No 3 0-1 Miles Pacific 47
## 323 Manual Yes 2 0-1 Miles Europe 41
## 324 Clerical No 0 0-1 Miles Europe 37
## 325 Professional Yes 0 1-2 Miles Pacific 38
## 326 Clerical No 2 0-1 Miles Europe 36
## 327 Clerical No 0 0-1 Miles Pacific 26
## 328 Skilled Manual Yes 2 0-1 Miles Europe 40
## 329 Clerical Yes 2 1-2 Miles Europe 36
## 330 Skilled Manual Yes 2 10+ Miles Europe 59
## 331 Professional Yes 3 10+ Miles Pacific 32
## 332 Manual No 2 0-1 Miles Europe 30
## 333 Manual No 2 1-2 Miles Europe 35
## 334 Professional Yes 4 5-10 Miles Europe 51
## 335 Professional Yes 1 5-10 Miles Pacific 47
## 336 Management No 2 0-1 Miles Pacific 39
## 337 Manual No 2 0-1 Miles Europe 34
## 338 Manual Yes 2 0-1 Miles Europe 32
## 339 Professional Yes 4 5-10 Miles Europe 50
## 340 Clerical Yes 0 0-1 Miles Europe 66
## 341 Clerical Yes 1 2-5 Miles Europe 30
## 342 Manual No 1 2-5 Miles Europe 32
## 343 Manual Yes 2 1-2 Miles Europe 35
## 344 Manual No 1 2-5 Miles Europe 32
## 345 Clerical No 1 2-5 Miles Europe 31
## 346 Clerical Yes 0 0-1 Miles Europe 50
## 347 Skilled Manual No 0 0-1 Miles Europe 43
## 348 Skilled Manual No 1 0-1 Miles Pacific 45
## 349 Manual Yes 2 0-1 Miles Europe 42
## 350 Clerical No 1 0-1 Miles Europe 29
## 351 Manual No 0 0-1 Miles Pacific 28
## 352 Manual Yes 1 0-1 Miles Europe 37
## 353 Professional Yes 2 2-5 Miles Europe 53
## 354 Clerical No 0 0-1 Miles Europe 38
## 355 Clerical No 1 1-2 Miles Europe 39
## 356 Professional Yes 3 10+ Miles Pacific 32
## 357 Professional Yes 3 0-1 Miles Europe 51
## 358 Manual Yes 2 1-2 Miles Europe 33
## 359 Management Yes 3 5-10 Miles Europe 58
## 360 Professional Yes 3 10+ Miles Pacific 30
## 361 Management Yes 0 2-5 Miles Pacific 48
## 362 Clerical No 2 0-1 Miles Europe 27
## 363 Skilled Manual Yes 1 0-1 Miles Europe 33
## 364 Management Yes 2 0-1 Miles Pacific 66
## 365 Manual Yes 1 0-1 Miles Europe 38
## 366 Clerical No 0 0-1 Miles Europe 38
## 367 Skilled Manual Yes 1 0-1 Miles Pacific 45
## 368 Professional Yes 3 5-10 Miles Europe 50
## 369 Clerical No 2 5-10 Miles Pacific 60
## 370 Manual No 1 0-1 Miles Europe 53
## 371 Professional Yes 1 10+ Miles Pacific 46
## 372 Management Yes 3 0-1 Miles Pacific 41
## 373 Skilled Manual Yes 1 0-1 Miles Europe 43
## 374 Manual No 1 2-5 Miles Europe 30
## 375 Professional Yes 4 1-2 Miles Pacific 38
## 376 Skilled Manual Yes 1 0-1 Miles Europe 89
## 377 Clerical Yes 0 0-1 Miles Europe 64
## 378 Professional No 3 5-10 Miles Europe 51
## 379 Clerical No 2 5-10 Miles Pacific 56
## 380 Professional Yes 2 5-10 Miles Pacific 43
## 381 Professional No 3 10+ Miles Pacific 30
## 382 Clerical Yes 2 5-10 Miles Pacific 69
## 383 Professional Yes 2 10+ Miles Europe 53
## 384 Clerical Yes 0 0-1 Miles Europe 37
## 385 Manual No 1 0-1 Miles Pacific 28
## 386 Clerical Yes 0 0-1 Miles Europe 43
## 387 Professional Yes 4 10+ Miles Pacific 34
## 388 Manual No 2 1-2 Miles Europe 34
## 389 Clerical Yes 0 0-1 Miles Europe 64
## 390 Professional Yes 1 1-2 Miles Pacific 41
## 391 Professional No 1 5-10 Miles Pacific 38
## 392 Professional No 1 0-1 Miles Pacific 41
## 393 Clerical No 0 0-1 Miles Europe 51
## 394 Manual Yes 2 1-2 Miles Europe 32
## 395 Clerical Yes 0 0-1 Miles Europe 38
## 396 Clerical Yes 0 0-1 Miles Europe 38
## 397 Professional Yes 1 2-5 Miles Pacific 38
## 398 Clerical Yes 2 5-10 Miles Pacific 58
## 399 Clerical Yes 1 1-2 Miles Europe 39
## 400 Management No 1 5-10 Miles Pacific 53
## 401 Management Yes 4 10+ Miles Europe 53
## 402 Clerical Yes 0 0-1 Miles Europe 80
## 403 Manual Yes 0 0-1 Miles Europe 44
## 404 Clerical Yes 0 0-1 Miles Europe 44
## 405 Skilled Manual Yes 2 5-10 Miles Pacific 54
## 406 Clerical Yes 0 0-1 Miles Europe 37
## 407 Skilled Manual Yes 0 0-1 Miles Europe 41
## 408 Professional No 0 0-1 Miles Pacific 36
## 409 Clerical Yes 0 0-1 Miles Europe 33
## 410 Professional Yes 4 0-1 Miles Europe 52
## 411 Manual Yes 1 0-1 Miles Europe 46
## 412 Skilled Manual Yes 2 5-10 Miles Pacific 43
## 413 Clerical Yes 0 0-1 Miles Europe 34
## 414 Clerical No 2 5-10 Miles Pacific 67
## 415 Clerical Yes 0 0-1 Miles Europe 35
## 416 Management Yes 3 0-1 Miles Pacific 40
## 417 Professional No 1 0-1 Miles Pacific 37
## 418 Clerical No 2 5-10 Miles Pacific 67
## 419 Skilled Manual Yes 2 0-1 Miles Europe 41
## 420 Manual Yes 1 0-1 Miles Europe 51
## 421 Management Yes 4 10+ Miles Europe 59
## 422 Manual Yes 0 1-2 Miles Europe 51
## 423 Management No 3 10+ Miles Pacific 32
## 424 Manual Yes 1 2-5 Miles Europe 34
## 425 Manual Yes 2 0-1 Miles Europe 43
## 426 Management Yes 2 0-1 Miles Pacific 67
## 427 Clerical No 1 2-5 Miles Europe 28
## 428 Management Yes 0 0-1 Miles Pacific 36
## 429 Management Yes 3 2-5 Miles Pacific 48
## 430 Clerical Yes 1 2-5 Miles Europe 31
## 431 Skilled Manual Yes 2 5-10 Miles Pacific 55
## 432 Manual Yes 0 0-1 Miles Pacific 28
## 433 Management Yes 3 10+ Miles Pacific 34
## 434 Clerical No 1 0-1 Miles Europe 26
## 435 Skilled Manual Yes 2 5-10 Miles Pacific 53
## 436 Clerical No 1 2-5 Miles Europe 68
## 437 Skilled Manual Yes 2 5-10 Miles Pacific 50
## 438 Clerical Yes 2 0-1 Miles Europe 28
## 439 Skilled Manual No 0 0-1 Miles Europe 40
## 440 Skilled Manual Yes 2 0-1 Miles Pacific 44
## 441 Professional No 3 10+ Miles Pacific 34
## 442 Skilled Manual Yes 2 5-10 Miles Pacific 52
## 443 Management Yes 0 0-1 Miles Pacific 36
## 444 Skilled Manual Yes 1 0-1 Miles Europe 43
## 445 Manual No 1 1-2 Miles Europe 32
## 446 Skilled Manual Yes 1 1-2 Miles Europe 32
## 447 Management Yes 1 10+ Miles Pacific 48
## 448 Skilled Manual Yes 0 1-2 Miles Europe 32
## 449 Clerical Yes 2 0-1 Miles Europe 46
## 450 Skilled Manual Yes 0 0-1 Miles Europe 42
## 451 Manual Yes 0 0-1 Miles Europe 36
## 452 Skilled Manual Yes 0 0-1 Miles Europe 41
## 453 Clerical No 2 0-1 Miles Pacific 69
## 454 Skilled Manual Yes 2 5-10 Miles Pacific 45
## 455 Manual No 1 2-5 Miles Europe 34
## 456 Professional No 1 2-5 Miles Europe 53
## 457 Professional No 4 5-10 Miles Europe 50
## 458 Manual Yes 0 0-1 Miles Europe 65
## 459 Professional Yes 4 10+ Miles Pacific 32
## 460 Professional No 3 10+ Miles Pacific 33
## 461 Manual Yes 2 1-2 Miles Europe 31
## 462 Management Yes 2 0-1 Miles Pacific 46
## 463 Clerical Yes 0 0-1 Miles Europe 39
## 464 Manual Yes 1 0-1 Miles Europe 40
## 465 Clerical Yes 0 0-1 Miles Europe 46
## 466 Management Yes 2 0-1 Miles Pacific 65
## 467 Clerical Yes 0 0-1 Miles Europe 47
## 468 Management No 3 0-1 Miles Pacific 46
## 469 Management Yes 3 0-1 Miles Pacific 40
## 470 Clerical Yes 0 0-1 Miles Europe 65
## 471 Manual No 1 1-2 Miles Europe 28
## 472 Professional No 2 5-10 Miles Pacific 43
## 473 Clerical Yes 0 0-1 Miles Europe 38
## 474 Clerical Yes 0 0-1 Miles Europe 47
## 475 Professional No 0 0-1 Miles Pacific 36
## 476 Skilled Manual No 2 1-2 Miles Pacific 60
## 477 Professional Yes 1 5-10 Miles Pacific 42
## 478 Skilled Manual No 2 1-2 Miles Pacific 50
## 479 Clerical Yes 0 0-1 Miles Europe 35
## 480 Skilled Manual Yes 1 0-1 Miles Europe 32
## 481 Professional Yes 1 5-10 Miles Pacific 46
## 482 Clerical Yes 0 1-2 Miles Europe 33
## 483 Clerical No 0 0-1 Miles Europe 36
## 484 Clerical Yes 0 0-1 Miles Europe 70
## 485 Clerical No 1 2-5 Miles Europe 31
## 486 Clerical Yes 2 0-1 Miles Europe 42
## 487 Skilled Manual Yes 4 10+ Miles Europe 58
## 488 Clerical Yes 0 0-1 Miles Europe 39
## 489 Manual Yes 2 1-2 Miles Europe 34
## 490 Manual Yes 2 0-1 Miles Europe 32
## 491 Professional Yes 0 2-5 Miles North America 46
## 492 Skilled Manual Yes 2 5-10 Miles North America 48
## 493 Clerical Yes 1 1-2 Miles North America 31
## 494 Management Yes 3 10+ Miles North America 60
## 495 Professional Yes 0 5-10 Miles North America 51
## 496 Professional Yes 2 10+ Miles North America 56
## 497 Skilled Manual Yes 1 2-5 Miles North America 40
## 498 Professional Yes 0 2-5 Miles North America 34
## 499 Skilled Manual Yes 1 2-5 Miles North America 48
## 500 Skilled Manual No 2 1-2 Miles North America 31
## 501 Professional Yes 1 2-5 Miles North America 47
## 502 Skilled Manual Yes 0 0-1 Miles North America 34
## 503 Skilled Manual Yes 1 5-10 Miles North America 29
## 504 Management Yes 4 2-5 Miles North America 44
## 505 Skilled Manual Yes 1 2-5 Miles North America 38
## 506 Professional Yes 4 0-1 Miles North America 40
## 507 Professional Yes 2 2-5 Miles North America 42
## 508 Clerical Yes 1 1-2 Miles North America 51
## 509 Skilled Manual No 2 1-2 Miles North America 29
## 510 Professional Yes 1 2-5 Miles North America 48
## 511 Professional No 1 2-5 Miles North America 37
## 512 Management Yes 0 5-10 Miles North America 66
## 513 Skilled Manual Yes 1 0-1 Miles North America 45
## 514 Management Yes 2 10+ Miles North America 61
## 515 Professional No 1 2-5 Miles North America 45
## 516 Professional Yes 2 2-5 Miles North America 47
## 517 Professional Yes 2 5-10 Miles North America 49
## 518 Professional No 0 0-1 Miles North America 47
## 519 Management Yes 1 1-2 Miles North America 34
## 520 Management Yes 2 1-2 Miles North America 64
## 521 Professional No 3 1-2 Miles North America 44
## 522 Professional Yes 2 10+ Miles North America 62
## 523 Professional No 1 0-1 Miles North America 47
## 524 Professional No 2 0-1 Miles North America 49
## 525 Management Yes 2 5-10 Miles North America 67
## 526 Management Yes 3 10+ Miles North America 59
## 527 Management Yes 2 1-2 Miles North America 44
## 528 Skilled Manual Yes 0 0-1 Miles North America 36
## 529 Skilled Manual Yes 1 5-10 Miles North America 28
## 530 Professional Yes 1 10+ Miles North America 57
## 531 Skilled Manual Yes 1 5-10 Miles North America 27
## 532 Clerical Yes 2 5-10 Miles North America 28
## 533 Professional No 1 0-1 Miles North America 44
## 534 Management Yes 2 10+ Miles North America 66
## 535 Professional Yes 2 10+ Miles North America 64
## 536 Skilled Manual Yes 3 10+ Miles North America 41
## 537 Skilled Manual Yes 1 0-1 Miles North America 41
## 538 Clerical Yes 1 1-2 Miles North America 49
## 539 Management Yes 0 0-1 Miles North America 42
## 540 Professional No 1 2-5 Miles North America 37
## 541 Management Yes 2 1-2 Miles North America 52
## 542 Skilled Manual Yes 0 1-2 Miles North America 34
## 543 Skilled Manual Yes 2 5-10 Miles North America 29
## 544 Professional Yes 2 2-5 Miles North America 53
## 545 Management No 4 1-2 Miles North America 40
## 546 Skilled Manual No 2 1-2 Miles North America 29
## 547 Professional Yes 2 2-5 Miles North America 43
## 548 Professional Yes 2 2-5 Miles North America 55
## 549 Skilled Manual No 0 0-1 Miles North America 48
## 550 Management Yes 3 0-1 Miles North America 45
## 551 Professional No 1 0-1 Miles Pacific 42
## 552 Management Yes 2 10+ Miles North America 63
## 553 Professional Yes 2 10+ Miles North America 54
## 554 Professional No 2 5-10 Miles North America 73
## 555 Professional Yes 0 2-5 Miles North America 31
## 556 Skilled Manual No 1 2-5 Miles North America 39
## 557 Management Yes 0 1-2 Miles North America 42
## 558 Clerical Yes 0 1-2 Miles North America 31
## 559 Skilled Manual Yes 2 0-1 Miles North America 41
## 560 Management Yes 0 10+ Miles North America 58
## 561 Professional Yes 0 0-1 Miles North America 40
## 562 Clerical No 2 0-1 Miles North America 48
## 563 Professional Yes 0 2-5 Miles North America 34
## 564 Skilled Manual Yes 1 5-10 Miles North America 28
## 565 Skilled Manual Yes 1 5-10 Miles North America 27
## 566 Professional No 2 5-10 Miles North America 54
## 567 Management Yes 2 5-10 Miles North America 70
## 568 Clerical Yes 1 1-2 Miles North America 48
## 569 Skilled Manual Yes 1 2-5 Miles North America 44
## 570 Management Yes 2 10+ Miles North America 69
## 571 Skilled Manual Yes 2 5-10 Miles North America 52
## 572 Skilled Manual Yes 2 2-5 Miles North America 55
## 573 Skilled Manual Yes 2 5-10 Miles North America 30
## 574 Management Yes 2 1-2 Miles North America 63
## 575 Management Yes 1 1-2 Miles North America 34
## 576 Professional Yes 1 10+ Miles North America 56
## 577 Skilled Manual Yes 1 5-10 Miles North America 31
## 578 Management Yes 4 0-1 Miles North America 38
## 579 Management Yes 2 2-5 Miles North America 59
## 580 Clerical No 2 0-1 Miles North America 32
## 581 Management Yes 2 10+ Miles North America 69
## 582 Skilled Manual Yes 1 5-10 Miles North America 28
## 583 Skilled Manual Yes 0 1-2 Miles North America 47
## 584 Management Yes 2 10+ Miles North America 66
## 585 Skilled Manual No 1 0-1 Miles North America 37
## 586 Management No 3 0-1 Miles North America 39
## 587 Professional No 2 1-2 Miles North America 51
## 588 Management Yes 3 1-2 Miles North America 40
## 589 Professional Yes 1 10+ Miles North America 51
## 590 Management Yes 0 10+ Miles North America 57
## 591 Professional No 0 0-1 Miles North America 35
## 592 Professional No 2 10+ Miles North America 61
## 593 Professional Yes 2 5-10 Miles North America 44
## 594 Professional Yes 0 5-10 Miles North America 49
## 595 Management Yes 2 5-10 Miles North America 70
## 596 Skilled Manual Yes 2 2-5 Miles North America 78
## 597 Professional Yes 1 1-2 Miles North America 45
## 598 Professional No 1 2-5 Miles North America 58
## 599 Management Yes 4 0-1 Miles North America 41
## 600 Professional Yes 1 2-5 Miles North America 57
## 601 Skilled Manual No 2 0-1 Miles North America 49
## 602 Professional No 2 0-1 Miles North America 43
## 603 Skilled Manual Yes 2 5-10 Miles North America 52
## 604 Professional Yes 0 0-1 Miles North America 35
## 605 Skilled Manual Yes 2 5-10 Miles North America 27
## 606 Professional Yes 0 5-10 Miles North America 52
## 607 Skilled Manual Yes 0 2-5 Miles North America 36
## 608 Professional Yes 3 10+ Miles North America 46
## 609 Skilled Manual Yes 2 5-10 Miles North America 52
## 610 Professional No 1 0-1 Miles North America 43
## 611 Skilled Manual Yes 1 2-5 Miles North America 44
## 612 Management Yes 1 1-2 Miles North America 34
## 613 Clerical Yes 2 5-10 Miles North America 27
## 614 Professional Yes 4 5-10 Miles North America 45
## 615 Professional Yes 4 1-2 Miles North America 45
## 616 Skilled Manual No 4 0-1 Miles North America 47
## 617 Skilled Manual Yes 0 1-2 Miles North America 47
## 618 Skilled Manual Yes 2 2-5 Miles North America 44
## 619 Clerical No 2 0-1 Miles North America 49
## 620 Skilled Manual Yes 1 5-10 Miles North America 30
## 621 Professional Yes 4 2-5 Miles North America 41
## 622 Management Yes 1 1-2 Miles North America 58
## 623 Professional Yes 1 2-5 Miles North America 47
## 624 Professional Yes 1 1-2 Miles North America 55
## 625 Skilled Manual No 2 0-1 Miles North America 27
## 626 Management Yes 2 1-2 Miles North America 67
## 627 Skilled Manual Yes 2 5-10 Miles North America 29
## 628 Management Yes 2 1-2 Miles North America 67
## 629 Professional No 1 1-2 Miles North America 51
## 630 Skilled Manual Yes 0 0-1 Miles North America 35
## 631 Skilled Manual No 2 1-2 Miles North America 30
## 632 Professional Yes 3 2-5 Miles North America 44
## 633 Skilled Manual Yes 0 1-2 Miles North America 48
## 634 Management Yes 2 0-1 Miles North America 45
## 635 Management No 2 1-2 Miles North America 66
## 636 Skilled Manual No 2 0-1 Miles North America 49
## 637 Professional Yes 3 5-10 Miles North America 43
## 638 Skilled Manual No 2 1-2 Miles North America 30
## 639 Management Yes 2 5-10 Miles North America 74
## 640 Management Yes 3 1-2 Miles North America 65
## 641 Professional Yes 2 2-5 Miles North America 56
## 642 Management Yes 2 10+ Miles North America 64
## 643 Professional Yes 2 5-10 Miles North America 50
## 644 Professional Yes 0 2-5 Miles North America 35
## 645 Skilled Manual Yes 3 10+ Miles North America 41
## 646 Skilled Manual Yes 0 0-1 Miles North America 39
## 647 Skilled Manual No 0 1-2 Miles North America 47
## 648 Skilled Manual Yes 2 5-10 Miles North America 31
## 649 Management No 1 2-5 Miles North America 58
## 650 Professional No 1 2-5 Miles North America 38
## 651 Management Yes 2 10+ Miles North America 67
## 652 Professional No 2 1-2 Miles North America 32
## 653 Professional No 3 5-10 Miles North America 45
## 654 Skilled Manual No 2 1-2 Miles North America 31
## 655 Skilled Manual No 2 1-2 Miles North America 31
## 656 Clerical Yes 1 0-1 Miles North America 31
## 657 Professional No 2 5-10 Miles North America 50
## 658 Skilled Manual Yes 1 0-1 Miles North America 44
## 659 Skilled Manual Yes 1 2-5 Miles North America 38
## 660 Management Yes 2 10+ Miles North America 63
## 661 Professional Yes 0 2-5 Miles North America 36
## 662 Skilled Manual No 2 0-1 Miles North America 28
## 663 Professional No 3 1-2 Miles North America 44
## 664 Professional Yes 1 0-1 Miles North America 47
## 665 Skilled Manual Yes 0 1-2 Miles North America 40
## 666 Management Yes 4 0-1 Miles North America 40
## 667 Skilled Manual Yes 1 2-5 Miles North America 46
## 668 Professional No 2 10+ Miles North America 61
## 669 Professional Yes 0 0-1 Miles North America 40
## 670 Professional Yes 2 5-10 Miles North America 50
## 671 Professional Yes 1 10+ Miles North America 59
## 672 Professional Yes 0 2-5 Miles North America 36
## 673 Skilled Manual Yes 2 5-10 Miles North America 30
## 674 Professional Yes 0 2-5 Miles North America 35
## 675 Skilled Manual Yes 2 1-2 Miles North America 48
## 676 Management Yes 4 0-1 Miles North America 41
## 677 Clerical Yes 1 0-1 Miles North America 47
## 678 Skilled Manual No 0 0-1 Miles North America 47
## 679 Management No 2 2-5 Miles Europe 62
## 680 Management Yes 2 10+ Miles North America 60
## 681 Skilled Manual No 1 1-2 Miles North America 33
## 682 Skilled Manual No 0 0-1 Miles North America 47
## 683 Clerical No 2 0-1 Miles North America 52
## 684 Professional Yes 3 2-5 Miles North America 40
## 685 Skilled Manual No 2 0-1 Miles North America 42
## 686 Management Yes 2 5-10 Miles North America 53
## 687 Clerical Yes 1 1-2 Miles North America 51
## 688 Skilled Manual Yes 2 5-10 Miles North America 30
## 689 Skilled Manual No 2 0-1 Miles North America 51
## 690 Skilled Manual Yes 2 5-10 Miles North America 26
## 691 Management No 1 2-5 Miles North America 45
## 692 Skilled Manual Yes 0 0-1 Miles North America 34
## 693 Professional Yes 1 2-5 Miles North America 44
## 694 Skilled Manual No 2 0-1 Miles North America 41
## 695 Professional No 0 0-1 Miles North America 36
## 696 Professional Yes 2 0-1 Miles North America 44
## 697 Professional No 2 1-2 Miles North America 30
## 698 Clerical No 2 0-1 Miles North America 28
## 699 Clerical Yes 2 1-2 Miles North America 49
## 700 Professional No 2 0-1 Miles North America 43
## 701 Management Yes 1 1-2 Miles North America 59
## 702 Skilled Manual Yes 2 5-10 Miles North America 26
## 703 Professional Yes 4 5-10 Miles North America 46
## 704 Skilled Manual Yes 0 1-2 Miles North America 33
## 705 Professional Yes 1 2-5 Miles North America 42
## 706 Management Yes 1 10+ Miles North America 59
## 707 Skilled Manual No 1 1-2 Miles North America 33
## 708 Skilled Manual Yes 1 0-1 Miles North America 44
## 709 Management Yes 4 10+ Miles North America 60
## 710 Management Yes 1 10+ Miles North America 59
## 711 Professional Yes 2 5-10 Miles North America 32
## 712 Professional Yes 1 10+ Miles North America 58
## 713 Professional No 2 2-5 Miles North America 59
## 714 Skilled Manual Yes 1 2-5 Miles North America 38
## 715 Skilled Manual Yes 2 5-10 Miles North America 28
## 716 Professional Yes 0 2-5 Miles North America 37
## 717 Skilled Manual No 0 0-1 Miles North America 40
## 718 Management Yes 1 1-2 Miles North America 38
## 719 Professional Yes 0 2-5 Miles North America 36
## 720 Professional Yes 2 0-1 Miles North America 37
## 721 Professional No 3 2-5 Miles North America 60
## 722 Management Yes 4 5-10 Miles North America 42
## 723 Management No 2 1-2 Miles North America 53
## 724 Skilled Manual Yes 2 5-10 Miles North America 49
## 725 Skilled Manual Yes 2 1-2 Miles North America 49
## 726 Management Yes 3 0-1 Miles North America 42
## 727 Manual No 2 0-1 Miles North America 53
## 728 Professional Yes 1 0-1 Miles North America 46
## 729 Skilled Manual Yes 2 5-10 Miles North America 27
## 730 Professional Yes 1 0-1 Miles North America 48
## 731 Skilled Manual Yes 2 2-5 Miles North America 41
## 732 Professional No 2 1-2 Miles North America 49
## 733 Professional Yes 1 2-5 Miles North America 38
## 734 Management No 4 0-1 Miles North America 44
## 735 Management No 3 0-1 Miles North America 45
## 736 Skilled Manual Yes 1 5-10 Miles North America 26
## 737 Skilled Manual Yes 1 5-10 Miles North America 31
## 738 Skilled Manual No 2 1-2 Miles North America 49
## 739 Clerical No 1 1-2 Miles North America 47
## 740 Professional Yes 1 10+ Miles North America 55
## 741 Clerical No 0 0-1 Miles North America 30
## 742 Clerical Yes 1 1-2 Miles North America 48
## 743 Skilled Manual Yes 2 5-10 Miles North America 30
## 744 Management Yes 3 5-10 Miles North America 45
## 745 Professional Yes 1 10+ Miles North America 56
## 746 Skilled Manual Yes 0 1-2 Miles North America 47
## 747 Management Yes 0 10+ Miles North America 56
## 748 Professional No 1 0-1 Miles North America 44
## 749 Management Yes 3 2-5 Miles North America 69
## 750 Professional Yes 1 2-5 Miles North America 59
## 751 Skilled Manual Yes 2 1-2 Miles North America 50
## 752 Professional Yes 0 2-5 Miles North America 36
## 753 Professional Yes 2 5-10 Miles North America 32
## 754 Skilled Manual No 1 1-2 Miles North America 27
## 755 Professional Yes 2 5-10 Miles North America 59
## 756 Professional No 2 2-5 Miles North America 53
## 757 Skilled Manual No 1 0-1 Miles North America 36
## 758 Clerical Yes 2 1-2 Miles North America 51
## 759 Skilled Manual No 0 0-1 Miles North America 47
## 760 Professional Yes 0 2-5 Miles North America 43
## 761 Clerical No 2 0-1 Miles North America 50
## 762 Management Yes 3 10+ Miles North America 59
## 763 Skilled Manual Yes 0 2-5 Miles North America 37
## 764 Skilled Manual Yes 0 0-1 Miles North America 33
## 765 Skilled Manual No 1 1-2 Miles North America 27
## 766 Skilled Manual Yes 2 5-10 Miles North America 34
## 767 Skilled Manual Yes 3 10+ Miles North America 42
## 768 Professional Yes 2 2-5 Miles North America 57
## 769 Professional No 4 2-5 Miles North America 45
## 770 Management Yes 4 0-1 Miles North America 40
## 771 Skilled Manual No 0 0-1 Miles North America 38
## 772 Skilled Manual No 1 0-1 Miles North America 47
## 773 Skilled Manual Yes 0 1-2 Miles North America 47
## 774 Skilled Manual Yes 0 0-1 Miles North America 34
## 775 Professional Yes 0 0-1 Miles North America 36
## 776 Skilled Manual Yes 2 10+ Miles North America 54
## 777 Management No 1 2-5 Miles North America 59
## 778 Skilled Manual Yes 2 5-10 Miles North America 27
## 779 Professional Yes 3 0-1 Miles North America 41
## 780 Professional No 2 2-5 Miles North America 50
## 781 Professional Yes 1 10+ Miles North America 55
## 782 Management Yes 0 0-1 Miles North America 43
## 783 Professional Yes 2 2-5 Miles North America 43
## 784 Skilled Manual Yes 3 5-10 Miles North America 42
## 785 Manual Yes 2 1-2 Miles North America 53
## 786 Skilled Manual No 2 0-1 Miles North America 28
## 787 Skilled Manual Yes 1 0-1 Miles North America 35
## 788 Management No 1 2-5 Miles North America 59
## 789 Clerical Yes 2 1-2 Miles North America 49
## 790 Professional No 2 1-2 Miles North America 48
## 791 Skilled Manual No 2 1-2 Miles North America 50
## 792 Skilled Manual Yes 2 5-10 Miles North America 28
## 793 Clerical No 1 5-10 Miles North America 52
## 794 Clerical Yes 1 2-5 Miles North America 52
## 795 Management Yes 2 5-10 Miles North America 69
## 796 Professional Yes 2 5-10 Miles North America 51
## 797 Professional Yes 2 1-2 Miles North America 57
## 798 Skilled Manual Yes 1 5-10 Miles North America 27
## 799 Skilled Manual No 2 0-1 Miles North America 25
## 800 Skilled Manual Yes 0 1-2 Miles North America 33
## 801 Professional Yes 2 2-5 Miles North America 43
## 802 Management Yes 2 5-10 Miles North America 73
## 803 Skilled Manual Yes 1 5-10 Miles North America 27
## 804 Skilled Manual Yes 2 5-10 Miles North America 28
## 805 Skilled Manual No 2 0-1 Miles North America 27
## 806 Skilled Manual Yes 2 5-10 Miles North America 31
## 807 Manual Yes 2 1-2 Miles North America 53
## 808 Professional No 2 1-2 Miles North America 32
## 809 Skilled Manual Yes 2 1-2 Miles North America 50
## 810 Professional Yes 2 5-10 Miles North America 69
## 811 Management Yes 2 5-10 Miles North America 52
## 812 Skilled Manual No 2 1-2 Miles North America 31
## 813 Management Yes 2 10+ Miles North America 61
## 814 Professional Yes 2 10+ Miles North America 53
## 815 Management Yes 2 1-2 Miles North America 62
## 816 Skilled Manual No 2 1-2 Miles North America 30
## 817 Professional Yes 0 2-5 Miles North America 43
## 818 Professional Yes 0 2-5 Miles North America 42
## 819 Skilled Manual Yes 1 5-10 Miles North America 30
## 820 Skilled Manual Yes 2 5-10 Miles North America 30
## 821 Management Yes 1 5-10 Miles North America 43
## 822 Skilled Manual Yes 2 5-10 Miles North America 33
## 823 Skilled Manual Yes 2 5-10 Miles North America 32
## 824 Professional Yes 0 5-10 Miles North America 50
## 825 Management No 3 0-1 Miles North America 37
## 826 Professional No 1 1-2 Miles North America 52
## 827 Professional Yes 0 2-5 Miles North America 36
## 828 Skilled Manual Yes 2 2-5 Miles North America 41
## 829 Clerical Yes 2 5-10 Miles North America 26
## 830 Management No 4 0-1 Miles North America 66
## 831 Professional No 2 5-10 Miles North America 51
## 832 Professional Yes 2 0-1 Miles North America 43
## 833 Professional Yes 0 0-1 Miles North America 39
## 834 Professional No 1 0-1 Miles North America 37
## 835 Skilled Manual No 2 2-5 Miles North America 54
## 836 Skilled Manual Yes 0 2-5 Miles North America 40
## 837 Skilled Manual Yes 2 5-10 Miles North America 28
## 838 Skilled Manual Yes 0 0-1 Miles North America 33
## 839 Skilled Manual Yes 2 2-5 Miles North America 41
## 840 Professional Yes 0 0-1 Miles North America 37
## 841 Professional Yes 2 10+ Miles North America 53
## 842 Management Yes 3 5-10 Miles North America 64
## 843 Skilled Manual Yes 1 2-5 Miles North America 45
## 844 Skilled Manual No 2 1-2 Miles North America 52
## 845 Professional Yes 2 10+ Miles North America 60
## 846 Clerical Yes 2 1-2 Miles North America 50
## 847 Professional No 1 1-2 Miles North America 56
## 848 Clerical Yes 2 5-10 Miles North America 29
## 849 Management No 2 0-1 Miles North America 38
## 850 Professional No 2 2-5 Miles North America 60
## 851 Management No 4 0-1 Miles North America 67
## 852 Skilled Manual Yes 1 5-10 Miles North America 32
## 853 Skilled Manual No 1 0-1 Miles North America 39
## 854 Professional Yes 0 2-5 Miles North America 35
## 855 Professional Yes 2 5-10 Miles North America 32
## 856 Skilled Manual No 1 1-2 Miles North America 31
## 857 Skilled Manual Yes 1 5-10 Miles North America 27
## 858 Professional Yes 1 0-1 Miles North America 47
## 859 Professional No 1 0-1 Miles North America 42
## 860 Skilled Manual Yes 2 1-2 Miles North America 49
## 861 Skilled Manual Yes 1 5-10 Miles North America 32
## 862 Manual No 2 1-2 Miles North America 53
## 863 Skilled Manual Yes 0 1-2 Miles North America 32
## 864 Management No 1 0-1 Miles North America 38
## 865 Skilled Manual Yes 2 5-10 Miles North America 31
## 866 Management No 1 0-1 Miles North America 38
## 867 Professional Yes 2 10+ Miles North America 55
## 868 Professional Yes 1 5-10 Miles North America 49
## 869 Skilled Manual Yes 3 10+ Miles North America 60
## 870 Management No 4 1-2 Miles North America 42
## 871 Skilled Manual Yes 1 0-1 Miles North America 46
## 872 Professional Yes 2 10+ Miles North America 55
## 873 Management Yes 2 5-10 Miles North America 53
## 874 Skilled Manual Yes 2 2-5 Miles North America 40
## 875 Skilled Manual Yes 1 5-10 Miles North America 53
## 876 Skilled Manual Yes 0 2-5 Miles North America 38
## 877 Clerical No 2 0-1 Miles North America 26
## 878 Management Yes 2 2-5 Miles North America 61
## 879 Management Yes 2 5-10 Miles North America 71
## 880 Professional Yes 2 1-2 Miles North America 45
## 881 Professional Yes 0 0-1 Miles North America 37
## 882 Management Yes 2 0-1 Miles North America 72
## 883 Skilled Manual Yes 0 0-1 Miles North America 32
## 884 Professional Yes 1 2-5 Miles North America 48
## 885 Management Yes 2 5-10 Miles North America 68
## 886 Clerical Yes 2 0-1 Miles North America 49
## 887 Professional Yes 0 2-5 Miles North America 34
## 888 Skilled Manual Yes 0 0-1 Miles North America 32
## 889 Skilled Manual No 2 0-1 Miles North America 42
## 890 Skilled Manual Yes 0 0-1 Miles North America 35
## 891 Clerical Yes 1 0-1 Miles North America 48
## 892 Management Yes 3 2-5 Miles North America 73
## 893 Skilled Manual Yes 2 2-5 Miles North America 43
## 894 Professional Yes 0 0-1 Miles North America 35
## 895 Professional Yes 0 0-1 Miles North America 35
## 896 Management Yes 2 1-2 Miles North America 64
## 897 Skilled Manual Yes 0 0-1 Miles North America 34
## 898 Clerical No 2 0-1 Miles North America 28
## 899 Management Yes 3 10+ Miles North America 60
## 900 Professional Yes 3 10+ Miles North America 46
## 901 Skilled Manual Yes 2 0-1 Miles North America 44
## 902 Skilled Manual Yes 2 2-5 Miles North America 42
## 903 Skilled Manual Yes 0 2-5 Miles North America 40
## 904 Management Yes 1 5-10 Miles North America 73
## 905 Skilled Manual No 0 0-1 Miles North America 36
## 906 Management Yes 1 1-2 Miles North America 38
## 907 Professional Yes 0 2-5 Miles North America 34
## 908 Management Yes 2 10+ Miles North America 63
## 909 Skilled Manual Yes 2 2-5 Miles North America 41
## 910 Skilled Manual Yes 0 1-2 Miles North America 39
## 911 Skilled Manual Yes 2 2-5 Miles North America 46
## 912 Management Yes 2 5-10 Miles North America 64
## 913 Clerical Yes 1 1-2 Miles North America 32
## 914 Skilled Manual Yes 0 2-5 Miles North America 36
## 915 Skilled Manual No 0 0-1 Miles North America 47
## 916 Management Yes 2 10+ Miles North America 64
## 917 Professional No 0 0-1 Miles North America 35
## 918 Management Yes 4 2-5 Miles North America 40
## 919 Skilled Manual Yes 2 5-10 Miles North America 34
## 920 Professional Yes 2 10+ Miles North America 61
## 921 Skilled Manual Yes 2 1-2 Miles North America 51
## 922 Professional Yes 1 5-10 Miles North America 49
## 923 Professional No 2 1-2 Miles North America 54
## 924 Management No 2 1-2 Miles North America 53
## 925 Professional Yes 1 2-5 Miles North America 48
## 926 Skilled Manual Yes 0 1-2 Miles North America 33
## 927 Professional Yes 2 10+ Miles North America 57
## 928 Professional Yes 0 2-5 Miles North America 39
## 929 Professional Yes 2 5-10 Miles North America 48
## 930 Professional Yes 2 5-10 Miles North America 50
## 931 Professional No 3 10+ Miles North America 47
## 932 Clerical Yes 1 1-2 Miles North America 49
## 933 Skilled Manual No 2 0-1 Miles North America 27
## 934 Skilled Manual Yes 1 5-10 Miles North America 29
## 935 Management Yes 0 2-5 Miles North America 59
## 936 Skilled Manual Yes 1 0-1 Miles North America 45
## 937 Management Yes 2 2-5 Miles North America 60
## 938 Professional Yes 0 0-1 Miles North America 36
## 939 Skilled Manual Yes 2 5-10 Miles North America 27
## 940 Skilled Manual No 2 1-2 Miles North America 50
## 941 Skilled Manual Yes 0 1-2 Miles North America 35
## 942 Skilled Manual Yes 0 2-5 Miles North America 34
## 943 Professional Yes 2 5-10 Miles North America 54
## 944 Skilled Manual Yes 2 0-1 Miles North America 42
## 945 Skilled Manual Yes 0 2-5 Miles North America 34
## 946 Skilled Manual No 1 0-1 Miles North America 38
## 947 Management Yes 2 1-2 Miles North America 63
## 948 Professional No 3 1-2 Miles North America 45
## 949 Skilled Manual No 0 0-1 Miles North America 40
## 950 Skilled Manual Yes 2 10+ Miles North America 53
## 951 Professional Yes 0 2-5 Miles North America 34
## 952 Professional No 1 0-1 Miles North America 38
## 953 Management No 1 1-2 Miles North America 59
## 954 Clerical Yes 1 1-2 Miles North America 30
## 955 Professional Yes 1 0-1 Miles North America 48
## 956 Skilled Manual Yes 2 2-5 Miles North America 43
## 957 Professional Yes 0 2-5 Miles North America 35
## 958 Professional Yes 2 5-10 Miles North America 30
## 959 Professional Yes 0 0-1 Miles North America 47
## 960 Skilled Manual Yes 1 2-5 Miles North America 45
## 961 Professional No 4 1-2 Miles North America 45
## 962 Management Yes 3 5-10 Miles North America 62
## 963 Professional Yes 2 10+ Miles North America 55
## 964 Management Yes 2 1-2 Miles North America 66
## 965 Professional Yes 1 10+ Miles North America 56
## 966 Skilled Manual No 1 0-1 Miles North America 40
## 967 Skilled Manual Yes 0 1-2 Miles North America 33
## 968 Management Yes 1 1-2 Miles North America 56
## 969 Clerical No 2 5-10 Miles North America 27
## 970 Professional No 0 0-1 Miles North America 39
## 971 Skilled Manual Yes 2 5-10 Miles North America 31
## 972 Skilled Manual No 2 1-2 Miles North America 51
## 973 Clerical Yes 1 5-10 Miles North America 52
## 974 Skilled Manual No 1 0-1 Miles North America 47
## 975 Management Yes 2 5-10 Miles North America 53
## 976 Professional Yes 0 0-1 Miles North America 35
## 977 Management Yes 2 10+ Miles North America 66
## 978 Management Yes 2 5-10 Miles North America 65
## 979 Professional Yes 3 5-10 Miles North America 45
## 980 Skilled Manual Yes 1 5-10 Miles North America 31
## 981 Skilled Manual Yes 3 10+ Miles North America 40
## 982 Professional Yes 4 2-5 Miles North America 46
## 983 Clerical No 1 1-2 Miles North America 47
## 984 Management Yes 2 0-1 Miles North America 41
## 985 Professional No 2 1-2 Miles North America 48
## 986 Skilled Manual Yes 2 0-1 Miles North America 42
## 987 Professional Yes 4 10+ Miles North America 41
## 988 Management Yes 2 10+ Miles North America 66
## 989 Management Yes 2 10+ Miles North America 63
## 990 Skilled Manual No 3 10+ Miles North America 42
## 991 Skilled Manual No 2 5-10 Miles North America 26
## 992 Professional Yes 0 2-5 Miles North America 36
## 993 Professional No 0 5-10 Miles North America 49
## 994 Professional No 3 0-1 Miles North America 44
## 995 Professional Yes 3 1-2 Miles North America 46
## 996 Professional Yes 2 2-5 Miles North America 54
## 997 Professional Yes 0 2-5 Miles North America 35
## 998 Skilled Manual Yes 0 0-1 Miles North America 38
## 999 Management No 3 1-2 Miles North America 38
## 1000 Professional Yes 2 10+ Miles North America 53
## purchased_bike id_imp marital_status_imp gender_imp income_imp
## 1 No FALSE FALSE FALSE FALSE
## 2 No FALSE FALSE FALSE FALSE
## 3 No FALSE FALSE FALSE FALSE
## 4 Yes FALSE FALSE TRUE FALSE
## 5 Yes FALSE FALSE FALSE FALSE
## 6 No FALSE FALSE FALSE FALSE
## 7 Yes FALSE FALSE FALSE FALSE
## 8 Yes FALSE FALSE FALSE FALSE
## 9 No FALSE TRUE FALSE FALSE
## 10 Yes FALSE FALSE FALSE TRUE
## 11 Yes FALSE FALSE FALSE FALSE
## 12 No FALSE FALSE FALSE FALSE
## 13 No FALSE FALSE FALSE FALSE
## 14 Yes FALSE FALSE FALSE FALSE
## 15 Yes FALSE FALSE FALSE FALSE
## 16 Yes FALSE FALSE FALSE FALSE
## 17 Yes FALSE FALSE FALSE FALSE
## 18 No FALSE FALSE FALSE FALSE
## 19 Yes FALSE FALSE FALSE FALSE
## 20 Yes FALSE FALSE FALSE FALSE
## 21 Yes FALSE FALSE FALSE FALSE
## 22 No FALSE FALSE FALSE FALSE
## 23 Yes FALSE FALSE FALSE FALSE
## 24 No FALSE FALSE FALSE FALSE
## 25 No FALSE FALSE FALSE FALSE
## 26 No FALSE FALSE FALSE FALSE
## 27 Yes FALSE FALSE FALSE FALSE
## 28 No FALSE TRUE FALSE FALSE
## 29 No FALSE FALSE FALSE FALSE
## 30 Yes FALSE FALSE FALSE FALSE
## 31 No FALSE FALSE FALSE FALSE
## 32 Yes FALSE FALSE FALSE FALSE
## 33 No FALSE FALSE FALSE FALSE
## 34 Yes FALSE FALSE FALSE FALSE
## 35 Yes FALSE FALSE FALSE FALSE
## 36 No FALSE FALSE FALSE FALSE
## 37 Yes FALSE FALSE FALSE FALSE
## 38 No FALSE FALSE FALSE FALSE
## 39 No FALSE FALSE FALSE FALSE
## 40 Yes FALSE FALSE FALSE FALSE
## 41 No FALSE FALSE FALSE FALSE
## 42 Yes FALSE FALSE FALSE FALSE
## 43 No FALSE FALSE FALSE FALSE
## 44 Yes FALSE FALSE FALSE FALSE
## 45 Yes FALSE FALSE FALSE FALSE
## 46 Yes FALSE FALSE FALSE FALSE
## 47 Yes FALSE FALSE FALSE FALSE
## 48 Yes FALSE FALSE FALSE FALSE
## 49 No FALSE FALSE FALSE FALSE
## 50 Yes FALSE TRUE FALSE FALSE
## 51 No FALSE FALSE FALSE FALSE
## 52 No FALSE FALSE FALSE FALSE
## 53 No FALSE FALSE FALSE FALSE
## 54 No FALSE FALSE FALSE FALSE
## 55 No FALSE FALSE FALSE FALSE
## 56 No FALSE FALSE FALSE FALSE
## 57 Yes FALSE FALSE FALSE FALSE
## 58 Yes FALSE FALSE FALSE FALSE
## 59 Yes FALSE FALSE FALSE FALSE
## 60 Yes FALSE FALSE FALSE FALSE
## 61 No FALSE FALSE FALSE FALSE
## 62 No FALSE FALSE FALSE FALSE
## 63 Yes FALSE FALSE FALSE FALSE
## 64 No FALSE FALSE FALSE FALSE
## 65 Yes FALSE FALSE FALSE FALSE
## 66 No FALSE FALSE FALSE FALSE
## 67 Yes FALSE FALSE FALSE FALSE
## 68 Yes FALSE FALSE FALSE FALSE
## 69 Yes FALSE FALSE FALSE FALSE
## 70 No FALSE FALSE FALSE FALSE
## 71 Yes FALSE FALSE FALSE FALSE
## 72 No FALSE FALSE FALSE FALSE
## 73 No FALSE FALSE FALSE FALSE
## 74 Yes FALSE FALSE FALSE FALSE
## 75 No FALSE FALSE FALSE FALSE
## 76 No FALSE FALSE FALSE FALSE
## 77 No FALSE FALSE FALSE FALSE
## 78 Yes FALSE FALSE FALSE FALSE
## 79 Yes FALSE FALSE FALSE FALSE
## 80 Yes FALSE FALSE FALSE FALSE
## 81 Yes FALSE FALSE FALSE FALSE
## 82 No FALSE FALSE FALSE FALSE
## 83 Yes FALSE FALSE FALSE FALSE
## 84 No FALSE FALSE FALSE FALSE
## 85 Yes FALSE FALSE FALSE FALSE
## 86 Yes FALSE FALSE FALSE FALSE
## 87 Yes FALSE FALSE FALSE FALSE
## 88 No FALSE FALSE FALSE FALSE
## 89 No FALSE FALSE FALSE FALSE
## 90 Yes FALSE FALSE FALSE FALSE
## 91 Yes FALSE FALSE FALSE FALSE
## 92 Yes FALSE FALSE FALSE FALSE
## 93 Yes FALSE FALSE FALSE FALSE
## 94 No FALSE FALSE FALSE FALSE
## 95 No FALSE FALSE FALSE FALSE
## 96 No FALSE FALSE FALSE FALSE
## 97 No FALSE FALSE FALSE FALSE
## 98 Yes FALSE FALSE FALSE FALSE
## 99 Yes FALSE TRUE FALSE FALSE
## 100 No FALSE FALSE FALSE FALSE
## 101 No FALSE FALSE FALSE FALSE
## 102 Yes FALSE FALSE FALSE FALSE
## 103 No FALSE FALSE FALSE FALSE
## 104 No FALSE FALSE FALSE FALSE
## 105 Yes FALSE FALSE FALSE FALSE
## 106 No FALSE FALSE FALSE FALSE
## 107 Yes FALSE FALSE FALSE FALSE
## 108 Yes FALSE FALSE FALSE FALSE
## 109 Yes FALSE FALSE FALSE FALSE
## 110 Yes FALSE FALSE FALSE FALSE
## 111 Yes FALSE FALSE FALSE TRUE
## 112 No FALSE FALSE FALSE FALSE
## 113 No FALSE FALSE FALSE FALSE
## 114 Yes FALSE FALSE FALSE FALSE
## 115 Yes FALSE FALSE FALSE FALSE
## 116 Yes FALSE FALSE FALSE FALSE
## 117 No FALSE FALSE FALSE FALSE
## 118 Yes FALSE FALSE FALSE FALSE
## 119 No FALSE FALSE FALSE FALSE
## 120 No FALSE FALSE FALSE FALSE
## 121 Yes FALSE FALSE FALSE FALSE
## 122 No FALSE FALSE FALSE FALSE
## 123 No FALSE FALSE FALSE FALSE
## 124 No FALSE FALSE FALSE FALSE
## 125 Yes FALSE FALSE FALSE FALSE
## 126 No FALSE FALSE FALSE FALSE
## 127 No FALSE FALSE FALSE FALSE
## 128 No FALSE FALSE FALSE FALSE
## 129 Yes FALSE FALSE FALSE FALSE
## 130 Yes FALSE FALSE FALSE FALSE
## 131 No FALSE FALSE FALSE FALSE
## 132 Yes FALSE FALSE FALSE FALSE
## 133 Yes FALSE FALSE FALSE FALSE
## 134 Yes FALSE FALSE FALSE FALSE
## 135 No FALSE FALSE FALSE FALSE
## 136 No FALSE FALSE FALSE FALSE
## 137 Yes FALSE FALSE FALSE FALSE
## 138 No FALSE FALSE FALSE FALSE
## 139 Yes FALSE FALSE FALSE FALSE
## 140 Yes FALSE FALSE FALSE FALSE
## 141 Yes FALSE FALSE FALSE FALSE
## 142 Yes FALSE FALSE FALSE FALSE
## 143 Yes FALSE FALSE FALSE FALSE
## 144 No FALSE FALSE FALSE FALSE
## 145 Yes FALSE FALSE FALSE FALSE
## 146 No FALSE FALSE FALSE FALSE
## 147 Yes FALSE FALSE FALSE FALSE
## 148 Yes FALSE FALSE FALSE FALSE
## 149 No FALSE FALSE FALSE FALSE
## 150 No FALSE FALSE FALSE FALSE
## 151 Yes FALSE TRUE FALSE FALSE
## 152 No FALSE FALSE FALSE FALSE
## 153 No FALSE FALSE FALSE FALSE
## 154 No FALSE FALSE FALSE FALSE
## 155 No FALSE FALSE TRUE FALSE
## 156 Yes FALSE FALSE FALSE FALSE
## 157 No FALSE FALSE FALSE FALSE
## 158 No FALSE FALSE FALSE FALSE
## 159 Yes FALSE FALSE FALSE FALSE
## 160 No FALSE FALSE FALSE FALSE
## 161 Yes FALSE FALSE FALSE FALSE
## 162 Yes FALSE FALSE FALSE FALSE
## 163 Yes FALSE FALSE FALSE FALSE
## 164 No FALSE FALSE FALSE FALSE
## 165 Yes FALSE FALSE FALSE FALSE
## 166 No FALSE FALSE FALSE FALSE
## 167 Yes FALSE FALSE FALSE FALSE
## 168 No FALSE FALSE FALSE FALSE
## 169 Yes FALSE FALSE FALSE FALSE
## 170 No FALSE FALSE FALSE FALSE
## 171 Yes FALSE FALSE FALSE FALSE
## 172 No FALSE FALSE FALSE FALSE
## 173 No FALSE FALSE FALSE FALSE
## 174 No FALSE FALSE FALSE FALSE
## 175 Yes FALSE FALSE FALSE FALSE
## 176 Yes FALSE FALSE FALSE FALSE
## 177 Yes FALSE FALSE FALSE FALSE
## 178 No FALSE FALSE FALSE FALSE
## 179 Yes FALSE FALSE FALSE FALSE
## 180 Yes FALSE FALSE FALSE FALSE
## 181 No FALSE FALSE FALSE FALSE
## 182 Yes FALSE FALSE FALSE FALSE
## 183 No FALSE FALSE FALSE FALSE
## 184 Yes FALSE FALSE FALSE FALSE
## 185 No FALSE FALSE FALSE FALSE
## 186 Yes FALSE FALSE FALSE FALSE
## 187 Yes FALSE FALSE FALSE FALSE
## 188 No FALSE FALSE FALSE FALSE
## 189 Yes FALSE FALSE FALSE FALSE
## 190 Yes FALSE FALSE FALSE FALSE
## 191 No FALSE FALSE FALSE FALSE
## 192 Yes FALSE FALSE FALSE TRUE
## 193 No FALSE FALSE FALSE FALSE
## 194 No FALSE FALSE FALSE FALSE
## 195 No FALSE FALSE FALSE FALSE
## 196 Yes FALSE FALSE FALSE FALSE
## 197 No FALSE FALSE FALSE FALSE
## 198 Yes FALSE FALSE FALSE FALSE
## 199 Yes FALSE FALSE FALSE FALSE
## 200 Yes FALSE FALSE FALSE FALSE
## 201 No FALSE FALSE FALSE FALSE
## 202 Yes FALSE FALSE FALSE FALSE
## 203 Yes FALSE FALSE FALSE FALSE
## 204 Yes FALSE FALSE FALSE FALSE
## 205 No FALSE FALSE FALSE FALSE
## 206 Yes FALSE FALSE FALSE FALSE
## 207 No FALSE FALSE FALSE FALSE
## 208 Yes FALSE FALSE FALSE FALSE
## 209 Yes FALSE FALSE FALSE FALSE
## 210 Yes FALSE FALSE FALSE FALSE
## 211 No FALSE FALSE FALSE FALSE
## 212 Yes FALSE FALSE FALSE FALSE
## 213 No FALSE FALSE FALSE FALSE
## 214 Yes FALSE FALSE FALSE FALSE
## 215 Yes FALSE FALSE FALSE FALSE
## 216 Yes FALSE FALSE FALSE FALSE
## 217 No FALSE FALSE FALSE FALSE
## 218 No FALSE FALSE FALSE FALSE
## 219 No FALSE FALSE FALSE FALSE
## 220 Yes FALSE FALSE FALSE FALSE
## 221 Yes FALSE FALSE FALSE FALSE
## 222 No FALSE FALSE FALSE FALSE
## 223 No FALSE FALSE FALSE FALSE
## 224 No FALSE FALSE FALSE FALSE
## 225 No FALSE FALSE FALSE FALSE
## 226 No FALSE FALSE FALSE FALSE
## 227 Yes FALSE FALSE FALSE FALSE
## 228 No FALSE FALSE FALSE FALSE
## 229 No FALSE FALSE FALSE FALSE
## 230 No FALSE FALSE FALSE FALSE
## 231 No FALSE FALSE FALSE FALSE
## 232 Yes FALSE FALSE FALSE FALSE
## 233 No FALSE FALSE FALSE FALSE
## 234 Yes FALSE FALSE FALSE FALSE
## 235 Yes FALSE TRUE FALSE FALSE
## 236 Yes FALSE FALSE FALSE FALSE
## 237 Yes FALSE FALSE FALSE FALSE
## 238 Yes FALSE FALSE FALSE FALSE
## 239 No FALSE FALSE FALSE FALSE
## 240 Yes FALSE FALSE FALSE FALSE
## 241 No FALSE FALSE FALSE FALSE
## 242 No FALSE FALSE FALSE FALSE
## 243 Yes FALSE FALSE FALSE FALSE
## 244 No FALSE FALSE FALSE FALSE
## 245 Yes FALSE FALSE FALSE FALSE
## 246 Yes FALSE FALSE FALSE FALSE
## 247 Yes FALSE FALSE FALSE FALSE
## 248 Yes FALSE FALSE FALSE FALSE
## 249 No FALSE FALSE FALSE FALSE
## 250 Yes FALSE FALSE FALSE FALSE
## 251 Yes FALSE FALSE FALSE FALSE
## 252 No FALSE FALSE FALSE FALSE
## 253 No FALSE FALSE FALSE FALSE
## 254 Yes FALSE FALSE FALSE FALSE
## 255 No FALSE FALSE FALSE FALSE
## 256 Yes FALSE FALSE FALSE FALSE
## 257 No FALSE FALSE FALSE FALSE
## 258 Yes FALSE FALSE FALSE FALSE
## 259 No FALSE FALSE FALSE FALSE
## 260 Yes FALSE FALSE FALSE FALSE
## 261 No FALSE FALSE FALSE FALSE
## 262 Yes FALSE FALSE FALSE FALSE
## 263 No FALSE FALSE FALSE FALSE
## 264 No FALSE FALSE FALSE FALSE
## 265 Yes FALSE FALSE FALSE FALSE
## 266 No FALSE FALSE FALSE FALSE
## 267 No FALSE FALSE FALSE FALSE
## 268 Yes FALSE FALSE FALSE FALSE
## 269 No FALSE FALSE FALSE FALSE
## 270 Yes FALSE FALSE FALSE FALSE
## 271 Yes FALSE FALSE FALSE FALSE
## 272 No FALSE FALSE FALSE FALSE
## 273 Yes FALSE FALSE FALSE FALSE
## 274 No FALSE FALSE FALSE FALSE
## 275 Yes FALSE FALSE FALSE FALSE
## 276 Yes FALSE FALSE FALSE FALSE
## 277 No FALSE FALSE FALSE FALSE
## 278 Yes FALSE FALSE FALSE FALSE
## 279 Yes FALSE FALSE FALSE FALSE
## 280 Yes FALSE FALSE FALSE FALSE
## 281 No FALSE FALSE FALSE FALSE
## 282 No FALSE FALSE FALSE FALSE
## 283 No FALSE FALSE FALSE FALSE
## 284 No FALSE FALSE FALSE FALSE
## 285 No FALSE FALSE FALSE FALSE
## 286 No FALSE FALSE FALSE FALSE
## 287 No FALSE FALSE FALSE FALSE
## 288 Yes FALSE FALSE FALSE FALSE
## 289 No FALSE FALSE FALSE FALSE
## 290 Yes FALSE FALSE FALSE FALSE
## 291 Yes FALSE FALSE FALSE FALSE
## 292 Yes FALSE FALSE FALSE FALSE
## 293 Yes FALSE FALSE FALSE FALSE
## 294 Yes FALSE FALSE FALSE FALSE
## 295 Yes FALSE FALSE FALSE FALSE
## 296 Yes FALSE FALSE FALSE FALSE
## 297 Yes FALSE FALSE FALSE FALSE
## 298 Yes FALSE FALSE FALSE FALSE
## 299 Yes FALSE FALSE FALSE FALSE
## 300 No FALSE FALSE FALSE FALSE
## 301 No FALSE FALSE FALSE FALSE
## 302 Yes FALSE TRUE FALSE TRUE
## 303 Yes FALSE FALSE FALSE FALSE
## 304 No FALSE FALSE FALSE FALSE
## 305 Yes FALSE FALSE FALSE FALSE
## 306 No FALSE FALSE FALSE FALSE
## 307 Yes FALSE FALSE FALSE FALSE
## 308 No FALSE FALSE FALSE FALSE
## 309 Yes FALSE FALSE FALSE FALSE
## 310 Yes FALSE FALSE FALSE FALSE
## 311 No FALSE FALSE FALSE FALSE
## 312 No FALSE FALSE FALSE FALSE
## 313 Yes FALSE FALSE FALSE FALSE
## 314 Yes FALSE FALSE FALSE FALSE
## 315 Yes FALSE FALSE FALSE FALSE
## 316 No FALSE FALSE FALSE FALSE
## 317 Yes FALSE FALSE FALSE FALSE
## 318 Yes FALSE FALSE FALSE FALSE
## 319 No FALSE FALSE FALSE FALSE
## 320 No FALSE FALSE FALSE FALSE
## 321 Yes FALSE FALSE FALSE FALSE
## 322 Yes FALSE FALSE FALSE FALSE
## 323 Yes FALSE FALSE FALSE FALSE
## 324 Yes FALSE FALSE FALSE FALSE
## 325 Yes FALSE FALSE FALSE FALSE
## 326 Yes FALSE FALSE FALSE FALSE
## 327 Yes FALSE FALSE FALSE FALSE
## 328 No FALSE FALSE FALSE FALSE
## 329 No FALSE FALSE FALSE FALSE
## 330 No FALSE FALSE FALSE FALSE
## 331 No FALSE FALSE FALSE FALSE
## 332 No FALSE FALSE FALSE FALSE
## 333 Yes FALSE FALSE FALSE FALSE
## 334 Yes FALSE FALSE FALSE FALSE
## 335 No FALSE FALSE FALSE FALSE
## 336 No FALSE FALSE TRUE FALSE
## 337 No FALSE FALSE FALSE FALSE
## 338 No FALSE FALSE FALSE FALSE
## 339 Yes FALSE FALSE FALSE FALSE
## 340 No FALSE FALSE FALSE FALSE
## 341 No FALSE FALSE FALSE FALSE
## 342 Yes FALSE FALSE FALSE FALSE
## 343 No FALSE FALSE FALSE FALSE
## 344 No FALSE FALSE FALSE FALSE
## 345 Yes FALSE FALSE FALSE FALSE
## 346 Yes FALSE FALSE FALSE FALSE
## 347 Yes FALSE FALSE FALSE FALSE
## 348 Yes FALSE FALSE FALSE FALSE
## 349 No FALSE FALSE FALSE FALSE
## 350 Yes FALSE FALSE FALSE FALSE
## 351 Yes FALSE FALSE FALSE FALSE
## 352 Yes FALSE FALSE FALSE FALSE
## 353 No FALSE FALSE FALSE FALSE
## 354 Yes FALSE FALSE FALSE FALSE
## 355 No FALSE FALSE FALSE FALSE
## 356 No FALSE FALSE FALSE FALSE
## 357 Yes FALSE FALSE FALSE FALSE
## 358 No FALSE FALSE FALSE FALSE
## 359 Yes FALSE FALSE FALSE FALSE
## 360 No FALSE FALSE FALSE FALSE
## 361 Yes FALSE FALSE FALSE FALSE
## 362 Yes FALSE FALSE FALSE FALSE
## 363 Yes FALSE FALSE FALSE FALSE
## 364 Yes FALSE FALSE FALSE FALSE
## 365 Yes FALSE FALSE FALSE FALSE
## 366 Yes FALSE FALSE FALSE FALSE
## 367 Yes FALSE FALSE FALSE FALSE
## 368 Yes FALSE FALSE FALSE FALSE
## 369 Yes FALSE FALSE FALSE FALSE
## 370 Yes FALSE FALSE FALSE FALSE
## 371 No FALSE FALSE FALSE FALSE
## 372 No FALSE FALSE FALSE FALSE
## 373 Yes FALSE FALSE FALSE FALSE
## 374 No FALSE FALSE FALSE FALSE
## 375 No FALSE FALSE FALSE FALSE
## 376 No FALSE FALSE FALSE FALSE
## 377 Yes FALSE FALSE FALSE FALSE
## 378 Yes FALSE FALSE FALSE FALSE
## 379 No FALSE FALSE FALSE FALSE
## 380 No FALSE FALSE FALSE FALSE
## 381 Yes FALSE FALSE FALSE FALSE
## 382 No FALSE FALSE FALSE FALSE
## 383 No FALSE FALSE FALSE FALSE
## 384 Yes FALSE FALSE FALSE FALSE
## 385 Yes FALSE FALSE FALSE FALSE
## 386 No FALSE FALSE FALSE FALSE
## 387 Yes FALSE FALSE FALSE FALSE
## 388 Yes FALSE FALSE FALSE FALSE
## 389 No FALSE FALSE FALSE FALSE
## 390 Yes FALSE FALSE FALSE FALSE
## 391 No FALSE FALSE FALSE FALSE
## 392 Yes FALSE FALSE FALSE FALSE
## 393 No FALSE FALSE FALSE FALSE
## 394 No FALSE FALSE FALSE FALSE
## 395 Yes FALSE FALSE FALSE FALSE
## 396 Yes FALSE FALSE FALSE FALSE
## 397 Yes FALSE FALSE FALSE FALSE
## 398 No FALSE FALSE FALSE FALSE
## 399 Yes FALSE FALSE FALSE FALSE
## 400 Yes FALSE FALSE FALSE FALSE
## 401 No FALSE FALSE FALSE FALSE
## 402 No FALSE FALSE FALSE FALSE
## 403 No FALSE FALSE FALSE FALSE
## 404 No FALSE FALSE FALSE FALSE
## 405 Yes FALSE FALSE FALSE FALSE
## 406 Yes FALSE FALSE FALSE FALSE
## 407 No FALSE FALSE FALSE FALSE
## 408 Yes FALSE FALSE FALSE FALSE
## 409 No FALSE FALSE FALSE FALSE
## 410 No FALSE FALSE FALSE FALSE
## 411 Yes FALSE FALSE FALSE FALSE
## 412 No FALSE FALSE FALSE FALSE
## 413 No FALSE FALSE FALSE FALSE
## 414 No FALSE FALSE FALSE FALSE
## 415 Yes FALSE FALSE FALSE FALSE
## 416 No FALSE FALSE FALSE FALSE
## 417 Yes FALSE FALSE FALSE FALSE
## 418 No FALSE FALSE FALSE FALSE
## 419 Yes FALSE FALSE FALSE FALSE
## 420 Yes FALSE FALSE FALSE FALSE
## 421 No FALSE FALSE FALSE FALSE
## 422 No FALSE FALSE FALSE FALSE
## 423 Yes FALSE FALSE FALSE FALSE
## 424 Yes FALSE FALSE FALSE FALSE
## 425 No FALSE FALSE FALSE FALSE
## 426 No FALSE FALSE FALSE FALSE
## 427 No FALSE FALSE FALSE FALSE
## 428 Yes FALSE FALSE FALSE FALSE
## 429 No FALSE FALSE FALSE FALSE
## 430 No FALSE FALSE FALSE FALSE
## 431 No FALSE FALSE FALSE FALSE
## 432 Yes FALSE FALSE FALSE FALSE
## 433 Yes FALSE FALSE FALSE FALSE
## 434 No FALSE FALSE FALSE FALSE
## 435 Yes FALSE FALSE FALSE FALSE
## 436 No FALSE FALSE FALSE FALSE
## 437 Yes FALSE FALSE FALSE FALSE
## 438 Yes FALSE FALSE FALSE FALSE
## 439 Yes FALSE FALSE FALSE FALSE
## 440 No FALSE FALSE FALSE FALSE
## 441 Yes FALSE FALSE FALSE FALSE
## 442 Yes FALSE FALSE FALSE TRUE
## 443 Yes FALSE FALSE FALSE FALSE
## 444 Yes FALSE FALSE FALSE FALSE
## 445 No FALSE FALSE FALSE FALSE
## 446 Yes FALSE FALSE FALSE FALSE
## 447 No FALSE FALSE FALSE FALSE
## 448 Yes FALSE FALSE FALSE FALSE
## 449 No FALSE FALSE FALSE FALSE
## 450 No FALSE FALSE FALSE FALSE
## 451 Yes FALSE FALSE FALSE FALSE
## 452 No FALSE FALSE FALSE FALSE
## 453 No FALSE FALSE FALSE FALSE
## 454 No FALSE FALSE FALSE FALSE
## 455 No FALSE FALSE FALSE FALSE
## 456 Yes FALSE FALSE FALSE FALSE
## 457 No FALSE FALSE FALSE FALSE
## 458 No FALSE FALSE FALSE FALSE
## 459 Yes FALSE FALSE FALSE FALSE
## 460 No FALSE FALSE FALSE FALSE
## 461 Yes FALSE FALSE FALSE FALSE
## 462 Yes FALSE FALSE FALSE FALSE
## 463 Yes FALSE FALSE FALSE FALSE
## 464 No FALSE FALSE FALSE FALSE
## 465 Yes FALSE FALSE FALSE FALSE
## 466 No FALSE FALSE FALSE FALSE
## 467 Yes FALSE FALSE FALSE FALSE
## 468 Yes FALSE FALSE FALSE FALSE
## 469 No FALSE FALSE FALSE FALSE
## 470 No FALSE FALSE FALSE FALSE
## 471 No FALSE FALSE FALSE FALSE
## 472 Yes FALSE FALSE FALSE FALSE
## 473 Yes FALSE FALSE FALSE FALSE
## 474 Yes FALSE FALSE FALSE FALSE
## 475 Yes FALSE FALSE FALSE FALSE
## 476 No FALSE FALSE FALSE FALSE
## 477 Yes FALSE FALSE FALSE FALSE
## 478 Yes FALSE FALSE FALSE FALSE
## 479 Yes FALSE FALSE FALSE FALSE
## 480 Yes FALSE FALSE FALSE FALSE
## 481 No FALSE FALSE FALSE FALSE
## 482 Yes FALSE FALSE FALSE FALSE
## 483 Yes FALSE FALSE FALSE FALSE
## 484 No FALSE FALSE FALSE FALSE
## 485 Yes FALSE FALSE FALSE FALSE
## 486 No FALSE FALSE FALSE FALSE
## 487 No FALSE FALSE FALSE FALSE
## 488 No FALSE FALSE FALSE FALSE
## 489 No FALSE FALSE FALSE FALSE
## 490 No FALSE FALSE FALSE FALSE
## 491 No FALSE FALSE FALSE FALSE
## 492 No FALSE FALSE FALSE FALSE
## 493 Yes FALSE FALSE FALSE FALSE
## 494 Yes FALSE FALSE FALSE FALSE
## 495 No FALSE FALSE FALSE FALSE
## 496 No FALSE FALSE FALSE FALSE
## 497 Yes FALSE FALSE FALSE FALSE
## 498 Yes FALSE FALSE FALSE FALSE
## 499 Yes FALSE FALSE FALSE FALSE
## 500 Yes FALSE FALSE FALSE FALSE
## 501 No FALSE FALSE FALSE FALSE
## 502 No FALSE FALSE FALSE FALSE
## 503 No FALSE FALSE FALSE FALSE
## 504 Yes FALSE FALSE FALSE FALSE
## 505 Yes FALSE FALSE FALSE FALSE
## 506 No FALSE FALSE FALSE FALSE
## 507 Yes FALSE FALSE FALSE FALSE
## 508 Yes FALSE FALSE FALSE FALSE
## 509 No FALSE FALSE FALSE FALSE
## 510 Yes FALSE FALSE FALSE TRUE
## 511 Yes FALSE FALSE FALSE FALSE
## 512 Yes FALSE FALSE FALSE FALSE
## 513 Yes FALSE FALSE FALSE FALSE
## 514 Yes FALSE FALSE FALSE FALSE
## 515 No FALSE FALSE FALSE FALSE
## 516 No FALSE FALSE FALSE FALSE
## 517 No FALSE FALSE FALSE FALSE
## 518 Yes FALSE FALSE FALSE FALSE
## 519 Yes FALSE FALSE FALSE FALSE
## 520 No FALSE FALSE FALSE FALSE
## 521 No FALSE FALSE FALSE FALSE
## 522 Yes FALSE FALSE FALSE FALSE
## 523 Yes FALSE FALSE FALSE FALSE
## 524 Yes FALSE FALSE FALSE FALSE
## 525 No FALSE FALSE FALSE FALSE
## 526 Yes FALSE FALSE FALSE FALSE
## 527 No FALSE FALSE FALSE FALSE
## 528 No FALSE FALSE FALSE FALSE
## 529 No FALSE FALSE FALSE FALSE
## 530 Yes FALSE FALSE FALSE FALSE
## 531 Yes FALSE FALSE FALSE FALSE
## 532 No FALSE FALSE FALSE FALSE
## 533 Yes FALSE FALSE FALSE FALSE
## 534 No FALSE FALSE FALSE FALSE
## 535 No FALSE FALSE FALSE FALSE
## 536 No FALSE FALSE FALSE FALSE
## 537 Yes FALSE FALSE FALSE FALSE
## 538 Yes FALSE FALSE FALSE FALSE
## 539 No FALSE FALSE FALSE FALSE
## 540 Yes FALSE FALSE FALSE FALSE
## 541 No FALSE FALSE FALSE FALSE
## 542 No FALSE FALSE FALSE FALSE
## 543 No FALSE FALSE FALSE FALSE
## 544 No FALSE FALSE FALSE FALSE
## 545 No FALSE FALSE FALSE FALSE
## 546 No FALSE FALSE FALSE FALSE
## 547 Yes FALSE FALSE FALSE FALSE
## 548 Yes FALSE FALSE FALSE FALSE
## 549 No FALSE FALSE FALSE FALSE
## 550 Yes FALSE FALSE FALSE FALSE
## 551 Yes FALSE FALSE FALSE FALSE
## 552 No FALSE FALSE FALSE FALSE
## 553 Yes FALSE FALSE FALSE FALSE
## 554 Yes FALSE FALSE FALSE FALSE
## 555 Yes FALSE FALSE FALSE FALSE
## 556 Yes FALSE FALSE FALSE FALSE
## 557 No FALSE FALSE FALSE FALSE
## 558 No FALSE FALSE FALSE FALSE
## 559 No FALSE FALSE FALSE FALSE
## 560 No FALSE FALSE FALSE FALSE
## 561 No FALSE FALSE FALSE FALSE
## 562 No FALSE FALSE FALSE FALSE
## 563 Yes FALSE FALSE FALSE FALSE
## 564 No FALSE FALSE FALSE FALSE
## 565 No FALSE FALSE FALSE FALSE
## 566 Yes FALSE FALSE FALSE FALSE
## 567 No FALSE FALSE FALSE FALSE
## 568 Yes FALSE FALSE FALSE FALSE
## 569 Yes FALSE FALSE FALSE FALSE
## 570 No FALSE FALSE FALSE FALSE
## 571 No FALSE FALSE FALSE FALSE
## 572 No FALSE FALSE FALSE FALSE
## 573 No FALSE FALSE FALSE FALSE
## 574 No FALSE FALSE FALSE FALSE
## 575 Yes FALSE FALSE FALSE FALSE
## 576 No FALSE FALSE FALSE FALSE
## 577 No FALSE FALSE FALSE FALSE
## 578 No FALSE FALSE FALSE FALSE
## 579 No FALSE FALSE FALSE FALSE
## 580 No FALSE FALSE FALSE FALSE
## 581 No FALSE FALSE FALSE FALSE
## 582 No FALSE FALSE FALSE FALSE
## 583 No FALSE FALSE FALSE FALSE
## 584 No FALSE FALSE FALSE FALSE
## 585 Yes FALSE FALSE FALSE FALSE
## 586 Yes FALSE FALSE FALSE FALSE
## 587 No FALSE FALSE FALSE FALSE
## 588 No FALSE FALSE FALSE FALSE
## 589 Yes FALSE FALSE FALSE FALSE
## 590 No FALSE FALSE FALSE FALSE
## 591 Yes FALSE FALSE FALSE FALSE
## 592 Yes FALSE FALSE FALSE FALSE
## 593 No FALSE FALSE FALSE FALSE
## 594 Yes FALSE FALSE FALSE FALSE
## 595 No FALSE FALSE FALSE FALSE
## 596 No FALSE FALSE FALSE FALSE
## 597 No FALSE FALSE FALSE FALSE
## 598 Yes FALSE FALSE FALSE FALSE
## 599 No FALSE FALSE FALSE FALSE
## 600 Yes FALSE FALSE FALSE FALSE
## 601 No FALSE FALSE FALSE FALSE
## 602 No FALSE FALSE TRUE FALSE
## 603 Yes FALSE FALSE FALSE FALSE
## 604 Yes FALSE FALSE FALSE FALSE
## 605 No FALSE FALSE FALSE FALSE
## 606 Yes FALSE FALSE FALSE FALSE
## 607 No FALSE FALSE FALSE FALSE
## 608 Yes FALSE FALSE FALSE FALSE
## 609 Yes FALSE FALSE FALSE FALSE
## 610 No FALSE FALSE FALSE FALSE
## 611 No FALSE FALSE FALSE FALSE
## 612 Yes FALSE FALSE FALSE FALSE
## 613 No FALSE FALSE FALSE FALSE
## 614 Yes FALSE FALSE FALSE FALSE
## 615 No FALSE FALSE FALSE FALSE
## 616 Yes FALSE FALSE FALSE FALSE
## 617 No FALSE FALSE FALSE FALSE
## 618 Yes FALSE FALSE FALSE FALSE
## 619 No FALSE FALSE FALSE FALSE
## 620 No FALSE FALSE FALSE FALSE
## 621 Yes FALSE FALSE FALSE FALSE
## 622 No FALSE FALSE FALSE FALSE
## 623 No FALSE FALSE FALSE FALSE
## 624 No FALSE FALSE FALSE FALSE
## 625 Yes FALSE FALSE FALSE FALSE
## 626 No FALSE FALSE FALSE FALSE
## 627 No FALSE FALSE FALSE FALSE
## 628 No FALSE FALSE FALSE FALSE
## 629 Yes FALSE FALSE FALSE FALSE
## 630 No FALSE FALSE FALSE FALSE
## 631 No FALSE FALSE FALSE FALSE
## 632 No FALSE FALSE FALSE FALSE
## 633 No FALSE FALSE FALSE FALSE
## 634 Yes FALSE FALSE FALSE FALSE
## 635 No FALSE FALSE FALSE FALSE
## 636 No FALSE FALSE FALSE FALSE
## 637 Yes FALSE FALSE FALSE FALSE
## 638 No FALSE FALSE FALSE FALSE
## 639 Yes FALSE FALSE FALSE FALSE
## 640 No FALSE FALSE FALSE FALSE
## 641 Yes FALSE FALSE FALSE FALSE
## 642 No FALSE FALSE FALSE FALSE
## 643 Yes FALSE FALSE FALSE FALSE
## 644 Yes FALSE FALSE FALSE FALSE
## 645 No FALSE FALSE FALSE FALSE
## 646 No FALSE FALSE FALSE FALSE
## 647 No FALSE FALSE FALSE FALSE
## 648 No FALSE FALSE FALSE FALSE
## 649 Yes FALSE FALSE FALSE FALSE
## 650 Yes FALSE FALSE FALSE FALSE
## 651 Yes FALSE FALSE FALSE FALSE
## 652 Yes FALSE FALSE FALSE FALSE
## 653 No FALSE FALSE FALSE FALSE
## 654 Yes FALSE FALSE FALSE FALSE
## 655 Yes FALSE FALSE FALSE FALSE
## 656 No FALSE FALSE FALSE FALSE
## 657 No FALSE FALSE FALSE FALSE
## 658 No FALSE FALSE FALSE FALSE
## 659 Yes FALSE FALSE FALSE FALSE
## 660 No FALSE FALSE FALSE FALSE
## 661 Yes FALSE FALSE FALSE FALSE
## 662 Yes FALSE FALSE FALSE FALSE
## 663 No FALSE FALSE FALSE FALSE
## 664 No FALSE FALSE FALSE FALSE
## 665 Yes FALSE FALSE FALSE FALSE
## 666 No FALSE FALSE FALSE FALSE
## 667 Yes FALSE FALSE FALSE FALSE
## 668 No FALSE FALSE FALSE FALSE
## 669 No FALSE FALSE FALSE FALSE
## 670 No FALSE FALSE FALSE FALSE
## 671 No FALSE FALSE FALSE FALSE
## 672 Yes FALSE FALSE FALSE FALSE
## 673 No FALSE FALSE FALSE FALSE
## 674 Yes FALSE FALSE FALSE FALSE
## 675 No FALSE FALSE FALSE FALSE
## 676 No FALSE FALSE FALSE FALSE
## 677 No FALSE FALSE FALSE FALSE
## 678 No FALSE FALSE FALSE FALSE
## 679 No FALSE FALSE FALSE FALSE
## 680 No FALSE FALSE FALSE FALSE
## 681 No FALSE FALSE FALSE FALSE
## 682 No FALSE FALSE FALSE FALSE
## 683 No FALSE FALSE FALSE FALSE
## 684 No FALSE FALSE FALSE FALSE
## 685 No FALSE FALSE FALSE FALSE
## 686 Yes FALSE FALSE FALSE FALSE
## 687 Yes FALSE FALSE FALSE FALSE
## 688 No FALSE FALSE FALSE FALSE
## 689 No FALSE FALSE TRUE FALSE
## 690 No FALSE FALSE FALSE FALSE
## 691 No FALSE FALSE FALSE FALSE
## 692 Yes FALSE FALSE FALSE FALSE
## 693 Yes FALSE FALSE FALSE FALSE
## 694 Yes FALSE FALSE FALSE FALSE
## 695 Yes FALSE FALSE FALSE FALSE
## 696 No FALSE FALSE TRUE FALSE
## 697 No FALSE FALSE FALSE FALSE
## 698 No FALSE FALSE FALSE FALSE
## 699 No FALSE FALSE FALSE FALSE
## 700 Yes FALSE FALSE FALSE FALSE
## 701 No FALSE FALSE FALSE FALSE
## 702 No FALSE FALSE FALSE FALSE
## 703 Yes FALSE FALSE FALSE FALSE
## 704 No FALSE FALSE FALSE FALSE
## 705 Yes FALSE FALSE FALSE FALSE
## 706 No FALSE FALSE FALSE FALSE
## 707 Yes FALSE FALSE FALSE FALSE
## 708 Yes FALSE FALSE FALSE FALSE
## 709 No FALSE FALSE FALSE FALSE
## 710 No FALSE FALSE FALSE FALSE
## 711 Yes FALSE FALSE FALSE FALSE
## 712 No FALSE FALSE FALSE FALSE
## 713 No FALSE FALSE FALSE FALSE
## 714 No FALSE FALSE FALSE FALSE
## 715 Yes FALSE FALSE FALSE FALSE
## 716 Yes FALSE FALSE FALSE FALSE
## 717 No FALSE FALSE FALSE FALSE
## 718 Yes FALSE FALSE FALSE FALSE
## 719 Yes FALSE FALSE FALSE FALSE
## 720 No FALSE FALSE FALSE FALSE
## 721 Yes FALSE FALSE FALSE FALSE
## 722 Yes FALSE FALSE FALSE FALSE
## 723 No FALSE FALSE FALSE FALSE
## 724 No FALSE FALSE FALSE FALSE
## 725 No FALSE FALSE FALSE FALSE
## 726 Yes FALSE FALSE FALSE FALSE
## 727 No FALSE FALSE FALSE FALSE
## 728 Yes FALSE FALSE FALSE FALSE
## 729 No FALSE FALSE FALSE FALSE
## 730 Yes FALSE FALSE FALSE FALSE
## 731 Yes FALSE FALSE FALSE FALSE
## 732 Yes FALSE FALSE FALSE FALSE
## 733 Yes FALSE FALSE FALSE FALSE
## 734 No FALSE FALSE FALSE FALSE
## 735 Yes FALSE FALSE FALSE FALSE
## 736 No FALSE FALSE FALSE FALSE
## 737 No FALSE FALSE FALSE FALSE
## 738 No FALSE FALSE FALSE FALSE
## 739 Yes FALSE FALSE FALSE FALSE
## 740 No FALSE FALSE FALSE FALSE
## 741 No FALSE FALSE FALSE FALSE
## 742 Yes FALSE FALSE FALSE FALSE
## 743 No FALSE FALSE FALSE FALSE
## 744 No FALSE FALSE FALSE FALSE
## 745 No FALSE FALSE FALSE FALSE
## 746 Yes FALSE FALSE FALSE FALSE
## 747 No FALSE FALSE FALSE FALSE
## 748 No FALSE FALSE FALSE FALSE
## 749 No FALSE FALSE FALSE FALSE
## 750 No FALSE FALSE FALSE FALSE
## 751 No FALSE FALSE FALSE FALSE
## 752 No FALSE FALSE FALSE FALSE
## 753 No FALSE FALSE FALSE FALSE
## 754 No FALSE FALSE FALSE FALSE
## 755 Yes FALSE FALSE FALSE FALSE
## 756 No FALSE FALSE FALSE FALSE
## 757 Yes FALSE FALSE FALSE FALSE
## 758 Yes FALSE FALSE FALSE FALSE
## 759 No FALSE FALSE FALSE FALSE
## 760 Yes FALSE FALSE FALSE FALSE
## 761 No FALSE FALSE FALSE FALSE
## 762 No FALSE FALSE FALSE FALSE
## 763 Yes FALSE FALSE FALSE FALSE
## 764 Yes FALSE FALSE FALSE FALSE
## 765 No FALSE FALSE FALSE FALSE
## 766 Yes FALSE FALSE FALSE FALSE
## 767 No FALSE FALSE FALSE FALSE
## 768 Yes FALSE FALSE FALSE FALSE
## 769 No FALSE FALSE FALSE FALSE
## 770 No FALSE FALSE FALSE FALSE
## 771 No FALSE FALSE FALSE FALSE
## 772 Yes FALSE FALSE FALSE FALSE
## 773 Yes FALSE FALSE FALSE FALSE
## 774 No FALSE FALSE FALSE FALSE
## 775 Yes FALSE FALSE FALSE FALSE
## 776 No FALSE FALSE FALSE FALSE
## 777 Yes FALSE FALSE FALSE FALSE
## 778 No FALSE FALSE FALSE FALSE
## 779 No FALSE FALSE FALSE FALSE
## 780 Yes FALSE FALSE FALSE FALSE
## 781 No FALSE FALSE FALSE FALSE
## 782 No FALSE FALSE FALSE FALSE
## 783 Yes FALSE FALSE FALSE FALSE
## 784 No FALSE FALSE FALSE FALSE
## 785 Yes FALSE FALSE FALSE FALSE
## 786 Yes FALSE FALSE FALSE FALSE
## 787 No FALSE FALSE FALSE FALSE
## 788 Yes FALSE FALSE FALSE FALSE
## 789 No FALSE FALSE FALSE FALSE
## 790 Yes FALSE FALSE FALSE FALSE
## 791 No FALSE FALSE FALSE FALSE
## 792 Yes FALSE FALSE FALSE FALSE
## 793 No FALSE FALSE FALSE FALSE
## 794 Yes FALSE FALSE FALSE FALSE
## 795 No FALSE FALSE FALSE FALSE
## 796 No FALSE FALSE FALSE FALSE
## 797 Yes FALSE FALSE FALSE FALSE
## 798 Yes FALSE FALSE FALSE FALSE
## 799 Yes FALSE FALSE FALSE FALSE
## 800 Yes FALSE FALSE FALSE FALSE
## 801 Yes FALSE FALSE FALSE FALSE
## 802 No FALSE FALSE FALSE FALSE
## 803 No FALSE FALSE FALSE FALSE
## 804 Yes FALSE FALSE FALSE FALSE
## 805 Yes FALSE FALSE FALSE FALSE
## 806 No FALSE FALSE FALSE FALSE
## 807 No FALSE FALSE FALSE FALSE
## 808 Yes FALSE FALSE FALSE FALSE
## 809 Yes FALSE FALSE FALSE FALSE
## 810 No FALSE FALSE FALSE FALSE
## 811 Yes FALSE FALSE FALSE FALSE
## 812 No FALSE FALSE FALSE FALSE
## 813 No FALSE FALSE FALSE FALSE
## 814 No FALSE FALSE FALSE FALSE
## 815 Yes FALSE FALSE FALSE FALSE
## 816 No FALSE FALSE FALSE FALSE
## 817 Yes FALSE FALSE FALSE FALSE
## 818 Yes FALSE FALSE FALSE FALSE
## 819 No FALSE FALSE FALSE FALSE
## 820 No FALSE FALSE FALSE FALSE
## 821 No FALSE FALSE FALSE FALSE
## 822 Yes FALSE FALSE FALSE FALSE
## 823 No FALSE FALSE FALSE FALSE
## 824 Yes FALSE FALSE FALSE FALSE
## 825 Yes FALSE FALSE FALSE FALSE
## 826 Yes FALSE FALSE FALSE FALSE
## 827 Yes FALSE FALSE FALSE FALSE
## 828 Yes FALSE FALSE FALSE FALSE
## 829 No FALSE FALSE FALSE FALSE
## 830 No FALSE FALSE FALSE FALSE
## 831 No FALSE FALSE FALSE FALSE
## 832 Yes FALSE FALSE FALSE FALSE
## 833 No FALSE FALSE FALSE FALSE
## 834 Yes FALSE FALSE FALSE FALSE
## 835 Yes FALSE FALSE FALSE FALSE
## 836 Yes FALSE FALSE FALSE FALSE
## 837 No FALSE FALSE FALSE FALSE
## 838 No FALSE FALSE FALSE FALSE
## 839 Yes FALSE FALSE FALSE FALSE
## 840 Yes FALSE FALSE FALSE FALSE
## 841 No FALSE FALSE FALSE FALSE
## 842 No FALSE FALSE FALSE FALSE
## 843 Yes FALSE FALSE FALSE FALSE
## 844 No FALSE FALSE FALSE FALSE
## 845 No FALSE FALSE FALSE FALSE
## 846 No FALSE FALSE FALSE FALSE
## 847 No FALSE FALSE FALSE FALSE
## 848 No FALSE FALSE FALSE FALSE
## 849 Yes FALSE FALSE FALSE FALSE
## 850 No FALSE FALSE FALSE FALSE
## 851 No FALSE FALSE FALSE FALSE
## 852 Yes FALSE FALSE FALSE FALSE
## 853 Yes FALSE FALSE FALSE FALSE
## 854 Yes FALSE FALSE FALSE FALSE
## 855 No FALSE FALSE FALSE FALSE
## 856 No FALSE FALSE FALSE FALSE
## 857 No FALSE FALSE FALSE FALSE
## 858 Yes FALSE FALSE FALSE FALSE
## 859 No FALSE FALSE FALSE FALSE
## 860 No FALSE FALSE FALSE FALSE
## 861 No FALSE FALSE FALSE FALSE
## 862 Yes FALSE FALSE FALSE FALSE
## 863 Yes FALSE FALSE FALSE FALSE
## 864 Yes FALSE FALSE FALSE FALSE
## 865 No FALSE FALSE FALSE FALSE
## 866 Yes FALSE FALSE FALSE FALSE
## 867 No FALSE FALSE FALSE FALSE
## 868 No FALSE FALSE TRUE FALSE
## 869 Yes FALSE FALSE FALSE FALSE
## 870 No FALSE FALSE FALSE FALSE
## 871 No FALSE FALSE FALSE FALSE
## 872 No FALSE FALSE FALSE FALSE
## 873 Yes FALSE FALSE FALSE FALSE
## 874 No FALSE FALSE FALSE FALSE
## 875 Yes FALSE FALSE FALSE FALSE
## 876 Yes FALSE FALSE FALSE FALSE
## 877 No FALSE FALSE FALSE FALSE
## 878 No FALSE FALSE FALSE FALSE
## 879 No FALSE FALSE FALSE FALSE
## 880 No FALSE FALSE FALSE FALSE
## 881 Yes FALSE FALSE FALSE FALSE
## 882 Yes FALSE FALSE FALSE FALSE
## 883 No FALSE FALSE FALSE FALSE
## 884 Yes FALSE FALSE FALSE FALSE
## 885 No FALSE FALSE FALSE FALSE
## 886 No FALSE FALSE FALSE FALSE
## 887 No FALSE FALSE FALSE FALSE
## 888 No FALSE FALSE FALSE FALSE
## 889 No FALSE FALSE FALSE FALSE
## 890 Yes FALSE FALSE FALSE FALSE
## 891 No FALSE FALSE FALSE FALSE
## 892 Yes FALSE FALSE FALSE FALSE
## 893 Yes FALSE FALSE FALSE FALSE
## 894 No FALSE FALSE FALSE FALSE
## 895 Yes FALSE FALSE FALSE FALSE
## 896 Yes FALSE FALSE FALSE FALSE
## 897 Yes FALSE FALSE FALSE FALSE
## 898 No FALSE FALSE FALSE FALSE
## 899 Yes FALSE FALSE FALSE FALSE
## 900 No FALSE FALSE FALSE FALSE
## 901 Yes FALSE FALSE FALSE FALSE
## 902 Yes FALSE FALSE FALSE FALSE
## 903 No FALSE FALSE FALSE FALSE
## 904 No FALSE FALSE FALSE FALSE
## 905 Yes FALSE FALSE FALSE FALSE
## 906 Yes FALSE FALSE FALSE FALSE
## 907 Yes FALSE FALSE FALSE FALSE
## 908 No FALSE FALSE FALSE FALSE
## 909 Yes FALSE FALSE TRUE FALSE
## 910 Yes FALSE FALSE FALSE FALSE
## 911 No FALSE FALSE FALSE FALSE
## 912 No FALSE FALSE FALSE FALSE
## 913 No FALSE FALSE FALSE FALSE
## 914 Yes FALSE FALSE FALSE FALSE
## 915 No FALSE FALSE FALSE FALSE
## 916 No FALSE FALSE FALSE FALSE
## 917 Yes FALSE FALSE FALSE FALSE
## 918 Yes FALSE FALSE FALSE FALSE
## 919 Yes FALSE FALSE FALSE FALSE
## 920 No FALSE FALSE FALSE FALSE
## 921 No FALSE FALSE FALSE FALSE
## 922 Yes FALSE FALSE FALSE FALSE
## 923 Yes FALSE FALSE FALSE FALSE
## 924 Yes FALSE FALSE FALSE FALSE
## 925 Yes FALSE FALSE FALSE FALSE
## 926 Yes FALSE FALSE FALSE FALSE
## 927 No FALSE FALSE FALSE FALSE
## 928 No FALSE FALSE FALSE FALSE
## 929 No FALSE FALSE FALSE FALSE
## 930 No FALSE FALSE FALSE FALSE
## 931 No FALSE FALSE FALSE FALSE
## 932 Yes FALSE FALSE FALSE FALSE
## 933 Yes FALSE FALSE FALSE FALSE
## 934 No FALSE FALSE FALSE FALSE
## 935 No FALSE FALSE FALSE FALSE
## 936 Yes FALSE FALSE FALSE FALSE
## 937 No FALSE FALSE FALSE FALSE
## 938 Yes FALSE FALSE FALSE FALSE
## 939 No FALSE FALSE FALSE FALSE
## 940 No FALSE FALSE FALSE FALSE
## 941 No FALSE FALSE FALSE FALSE
## 942 Yes FALSE FALSE FALSE FALSE
## 943 No FALSE FALSE FALSE FALSE
## 944 No FALSE FALSE FALSE FALSE
## 945 Yes FALSE FALSE FALSE FALSE
## 946 Yes FALSE FALSE FALSE FALSE
## 947 Yes FALSE FALSE FALSE FALSE
## 948 Yes FALSE FALSE FALSE FALSE
## 949 No FALSE FALSE FALSE FALSE
## 950 No FALSE FALSE FALSE FALSE
## 951 No FALSE FALSE FALSE FALSE
## 952 No FALSE FALSE TRUE FALSE
## 953 No FALSE FALSE FALSE FALSE
## 954 Yes FALSE FALSE FALSE FALSE
## 955 Yes FALSE FALSE FALSE FALSE
## 956 No FALSE FALSE FALSE FALSE
## 957 Yes FALSE FALSE FALSE FALSE
## 958 No FALSE FALSE FALSE FALSE
## 959 Yes FALSE FALSE FALSE FALSE
## 960 Yes FALSE FALSE FALSE FALSE
## 961 No FALSE FALSE FALSE FALSE
## 962 No FALSE FALSE FALSE FALSE
## 963 No FALSE FALSE FALSE FALSE
## 964 Yes FALSE FALSE FALSE FALSE
## 965 No FALSE FALSE FALSE FALSE
## 966 No FALSE FALSE FALSE FALSE
## 967 Yes FALSE FALSE FALSE FALSE
## 968 No FALSE FALSE FALSE FALSE
## 969 No FALSE FALSE FALSE FALSE
## 970 No FALSE FALSE FALSE FALSE
## 971 No FALSE FALSE FALSE FALSE
## 972 No FALSE FALSE FALSE FALSE
## 973 No FALSE FALSE FALSE FALSE
## 974 No FALSE FALSE TRUE FALSE
## 975 Yes FALSE FALSE FALSE FALSE
## 976 Yes FALSE FALSE FALSE FALSE
## 977 No FALSE FALSE FALSE FALSE
## 978 No FALSE FALSE FALSE FALSE
## 979 No FALSE FALSE FALSE FALSE
## 980 No FALSE FALSE FALSE FALSE
## 981 Yes FALSE FALSE FALSE FALSE
## 982 No FALSE FALSE FALSE FALSE
## 983 Yes FALSE FALSE FALSE FALSE
## 984 No FALSE FALSE FALSE FALSE
## 985 Yes FALSE FALSE FALSE FALSE
## 986 No FALSE FALSE FALSE FALSE
## 987 Yes FALSE FALSE FALSE FALSE
## 988 No FALSE FALSE FALSE FALSE
## 989 No FALSE FALSE FALSE FALSE
## 990 No FALSE FALSE FALSE FALSE
## 991 No FALSE FALSE FALSE FALSE
## 992 Yes FALSE FALSE FALSE FALSE
## 993 Yes FALSE FALSE FALSE FALSE
## 994 Yes FALSE FALSE FALSE FALSE
## 995 No FALSE FALSE FALSE FALSE
## 996 Yes FALSE FALSE FALSE FALSE
## 997 Yes FALSE FALSE FALSE FALSE
## 998 Yes FALSE FALSE TRUE FALSE
## 999 No FALSE FALSE FALSE FALSE
## 1000 Yes FALSE FALSE FALSE FALSE
## children_imp education_imp occupation_imp home_owner_imp cars_imp
## 1 FALSE FALSE FALSE FALSE FALSE
## 2 FALSE FALSE FALSE FALSE FALSE
## 3 FALSE FALSE FALSE FALSE FALSE
## 4 FALSE FALSE FALSE FALSE FALSE
## 5 FALSE FALSE FALSE FALSE FALSE
## 6 FALSE FALSE FALSE FALSE FALSE
## 7 FALSE FALSE FALSE TRUE FALSE
## 8 FALSE FALSE FALSE FALSE FALSE
## 9 FALSE FALSE FALSE FALSE FALSE
## 10 FALSE FALSE FALSE FALSE FALSE
## 11 FALSE FALSE FALSE FALSE FALSE
## 12 FALSE FALSE FALSE FALSE FALSE
## 13 FALSE FALSE FALSE FALSE TRUE
## 14 FALSE FALSE FALSE FALSE FALSE
## 15 FALSE FALSE FALSE FALSE FALSE
## 16 FALSE FALSE FALSE FALSE FALSE
## 17 FALSE FALSE FALSE FALSE FALSE
## 18 FALSE FALSE FALSE FALSE FALSE
## 19 FALSE FALSE FALSE FALSE FALSE
## 20 FALSE FALSE FALSE FALSE FALSE
## 21 FALSE FALSE FALSE FALSE FALSE
## 22 FALSE FALSE FALSE FALSE FALSE
## 23 FALSE FALSE FALSE FALSE FALSE
## 24 FALSE FALSE FALSE FALSE FALSE
## 25 FALSE FALSE FALSE FALSE FALSE
## 26 FALSE FALSE FALSE FALSE FALSE
## 27 FALSE FALSE FALSE FALSE FALSE
## 28 FALSE FALSE FALSE FALSE FALSE
## 29 FALSE FALSE FALSE FALSE FALSE
## 30 FALSE FALSE FALSE FALSE FALSE
## 31 FALSE FALSE FALSE FALSE FALSE
## 32 FALSE FALSE FALSE FALSE FALSE
## 33 FALSE FALSE FALSE FALSE FALSE
## 34 FALSE FALSE FALSE FALSE FALSE
## 35 FALSE FALSE FALSE FALSE FALSE
## 36 FALSE FALSE FALSE FALSE FALSE
## 37 FALSE FALSE FALSE FALSE FALSE
## 38 FALSE FALSE FALSE FALSE FALSE
## 39 FALSE FALSE FALSE FALSE FALSE
## 40 FALSE FALSE FALSE FALSE FALSE
## 41 FALSE FALSE FALSE FALSE FALSE
## 42 FALSE FALSE FALSE FALSE FALSE
## 43 FALSE FALSE FALSE FALSE FALSE
## 44 FALSE FALSE FALSE FALSE FALSE
## 45 FALSE FALSE FALSE FALSE FALSE
## 46 FALSE FALSE FALSE FALSE FALSE
## 47 FALSE FALSE FALSE FALSE FALSE
## 48 FALSE FALSE FALSE FALSE FALSE
## 49 FALSE FALSE FALSE FALSE FALSE
## 50 FALSE FALSE FALSE FALSE FALSE
## 51 FALSE FALSE FALSE FALSE FALSE
## 52 FALSE FALSE FALSE FALSE FALSE
## 53 FALSE FALSE FALSE FALSE FALSE
## 54 FALSE FALSE FALSE FALSE FALSE
## 55 FALSE FALSE FALSE FALSE FALSE
## 56 FALSE FALSE FALSE FALSE FALSE
## 57 FALSE FALSE FALSE FALSE FALSE
## 58 FALSE FALSE FALSE FALSE FALSE
## 59 FALSE FALSE FALSE FALSE FALSE
## 60 FALSE FALSE FALSE FALSE FALSE
## 61 FALSE FALSE FALSE FALSE FALSE
## 62 FALSE FALSE FALSE FALSE FALSE
## 63 FALSE FALSE FALSE FALSE FALSE
## 64 FALSE FALSE FALSE FALSE FALSE
## 65 FALSE FALSE FALSE FALSE FALSE
## 66 FALSE FALSE FALSE FALSE FALSE
## 67 FALSE FALSE FALSE FALSE FALSE
## 68 FALSE FALSE FALSE FALSE FALSE
## 69 FALSE FALSE FALSE FALSE FALSE
## 70 FALSE FALSE FALSE FALSE FALSE
## 71 FALSE FALSE FALSE FALSE FALSE
## 72 FALSE FALSE FALSE FALSE FALSE
## 73 FALSE FALSE FALSE FALSE FALSE
## 74 FALSE FALSE FALSE FALSE FALSE
## 75 FALSE FALSE FALSE FALSE FALSE
## 76 FALSE FALSE FALSE FALSE FALSE
## 77 FALSE FALSE FALSE FALSE FALSE
## 78 FALSE FALSE FALSE FALSE FALSE
## 79 FALSE FALSE FALSE FALSE FALSE
## 80 FALSE FALSE FALSE FALSE FALSE
## 81 FALSE FALSE FALSE FALSE FALSE
## 82 FALSE FALSE FALSE FALSE FALSE
## 83 FALSE FALSE FALSE FALSE FALSE
## 84 FALSE FALSE FALSE FALSE FALSE
## 85 FALSE FALSE FALSE FALSE FALSE
## 86 FALSE FALSE FALSE FALSE FALSE
## 87 FALSE FALSE FALSE FALSE FALSE
## 88 FALSE FALSE FALSE FALSE FALSE
## 89 FALSE FALSE FALSE FALSE FALSE
## 90 FALSE FALSE FALSE FALSE FALSE
## 91 FALSE FALSE FALSE FALSE FALSE
## 92 FALSE FALSE FALSE FALSE FALSE
## 93 FALSE FALSE FALSE FALSE FALSE
## 94 FALSE FALSE FALSE FALSE FALSE
## 95 FALSE FALSE FALSE FALSE FALSE
## 96 FALSE FALSE FALSE FALSE FALSE
## 97 FALSE FALSE FALSE FALSE FALSE
## 98 FALSE FALSE FALSE FALSE FALSE
## 99 FALSE FALSE FALSE FALSE FALSE
## 100 FALSE FALSE FALSE FALSE FALSE
## 101 FALSE FALSE FALSE FALSE FALSE
## 102 FALSE FALSE FALSE FALSE FALSE
## 103 FALSE FALSE FALSE FALSE FALSE
## 104 FALSE FALSE FALSE FALSE FALSE
## 105 FALSE FALSE FALSE FALSE FALSE
## 106 FALSE FALSE FALSE FALSE FALSE
## 107 FALSE FALSE FALSE FALSE FALSE
## 108 FALSE FALSE FALSE FALSE FALSE
## 109 FALSE FALSE FALSE FALSE FALSE
## 110 FALSE FALSE FALSE FALSE FALSE
## 111 FALSE FALSE FALSE FALSE FALSE
## 112 FALSE FALSE FALSE FALSE FALSE
## 113 FALSE FALSE FALSE FALSE FALSE
## 114 FALSE FALSE FALSE FALSE FALSE
## 115 FALSE FALSE FALSE FALSE FALSE
## 116 FALSE FALSE FALSE FALSE FALSE
## 117 FALSE FALSE FALSE FALSE FALSE
## 118 TRUE FALSE FALSE FALSE FALSE
## 119 FALSE FALSE FALSE FALSE FALSE
## 120 FALSE FALSE FALSE FALSE FALSE
## 121 FALSE FALSE FALSE FALSE FALSE
## 122 FALSE FALSE FALSE FALSE FALSE
## 123 FALSE FALSE FALSE FALSE FALSE
## 124 FALSE FALSE FALSE FALSE FALSE
## 125 FALSE FALSE FALSE FALSE FALSE
## 126 FALSE FALSE FALSE FALSE FALSE
## 127 FALSE FALSE FALSE FALSE FALSE
## 128 FALSE FALSE FALSE FALSE FALSE
## 129 FALSE FALSE FALSE FALSE FALSE
## 130 FALSE FALSE FALSE FALSE FALSE
## 131 FALSE FALSE FALSE FALSE FALSE
## 132 FALSE FALSE FALSE FALSE FALSE
## 133 FALSE FALSE FALSE FALSE FALSE
## 134 FALSE FALSE FALSE FALSE FALSE
## 135 FALSE FALSE FALSE FALSE FALSE
## 136 FALSE FALSE FALSE FALSE FALSE
## 137 FALSE FALSE FALSE FALSE FALSE
## 138 FALSE FALSE FALSE FALSE FALSE
## 139 FALSE FALSE FALSE FALSE FALSE
## 140 FALSE FALSE FALSE FALSE FALSE
## 141 FALSE FALSE FALSE FALSE FALSE
## 142 FALSE FALSE FALSE FALSE FALSE
## 143 FALSE FALSE FALSE FALSE FALSE
## 144 FALSE FALSE FALSE FALSE FALSE
## 145 FALSE FALSE FALSE FALSE FALSE
## 146 FALSE FALSE FALSE FALSE FALSE
## 147 FALSE FALSE FALSE FALSE FALSE
## 148 FALSE FALSE FALSE FALSE FALSE
## 149 FALSE FALSE FALSE FALSE FALSE
## 150 FALSE FALSE FALSE FALSE FALSE
## 151 FALSE FALSE FALSE FALSE FALSE
## 152 FALSE FALSE FALSE FALSE FALSE
## 153 FALSE FALSE FALSE FALSE FALSE
## 154 FALSE FALSE FALSE FALSE FALSE
## 155 FALSE FALSE FALSE FALSE FALSE
## 156 FALSE FALSE FALSE FALSE FALSE
## 157 FALSE FALSE FALSE FALSE FALSE
## 158 FALSE FALSE FALSE FALSE FALSE
## 159 FALSE FALSE FALSE FALSE FALSE
## 160 FALSE FALSE FALSE FALSE FALSE
## 161 FALSE FALSE FALSE FALSE FALSE
## 162 FALSE FALSE FALSE FALSE FALSE
## 163 FALSE FALSE FALSE FALSE FALSE
## 164 FALSE FALSE FALSE FALSE FALSE
## 165 FALSE FALSE FALSE FALSE FALSE
## 166 FALSE FALSE FALSE FALSE FALSE
## 167 FALSE FALSE FALSE FALSE FALSE
## 168 FALSE FALSE FALSE FALSE FALSE
## 169 FALSE FALSE FALSE FALSE FALSE
## 170 FALSE FALSE FALSE FALSE FALSE
## 171 FALSE FALSE FALSE FALSE FALSE
## 172 FALSE FALSE FALSE FALSE FALSE
## 173 FALSE FALSE FALSE FALSE FALSE
## 174 FALSE FALSE FALSE FALSE FALSE
## 175 FALSE FALSE FALSE FALSE FALSE
## 176 FALSE FALSE FALSE FALSE FALSE
## 177 FALSE FALSE FALSE FALSE FALSE
## 178 FALSE FALSE FALSE FALSE FALSE
## 179 FALSE FALSE FALSE FALSE FALSE
## 180 FALSE FALSE FALSE FALSE FALSE
## 181 FALSE FALSE FALSE FALSE FALSE
## 182 FALSE FALSE FALSE FALSE FALSE
## 183 FALSE FALSE FALSE FALSE FALSE
## 184 FALSE FALSE FALSE FALSE FALSE
## 185 FALSE FALSE FALSE FALSE FALSE
## 186 FALSE FALSE FALSE FALSE FALSE
## 187 FALSE FALSE FALSE FALSE FALSE
## 188 FALSE FALSE FALSE FALSE FALSE
## 189 FALSE FALSE FALSE FALSE FALSE
## 190 FALSE FALSE FALSE FALSE FALSE
## 191 FALSE FALSE FALSE FALSE FALSE
## 192 FALSE FALSE FALSE FALSE FALSE
## 193 FALSE FALSE FALSE FALSE FALSE
## 194 FALSE FALSE FALSE FALSE FALSE
## 195 FALSE FALSE FALSE FALSE FALSE
## 196 FALSE FALSE FALSE FALSE FALSE
## 197 FALSE FALSE FALSE FALSE TRUE
## 198 FALSE FALSE FALSE FALSE FALSE
## 199 FALSE FALSE FALSE FALSE FALSE
## 200 FALSE FALSE FALSE FALSE FALSE
## 201 FALSE FALSE FALSE FALSE FALSE
## 202 FALSE FALSE FALSE FALSE FALSE
## 203 FALSE FALSE FALSE FALSE TRUE
## 204 FALSE FALSE FALSE FALSE FALSE
## 205 FALSE FALSE FALSE FALSE FALSE
## 206 FALSE FALSE FALSE FALSE FALSE
## 207 FALSE FALSE FALSE FALSE FALSE
## 208 FALSE FALSE FALSE FALSE FALSE
## 209 FALSE FALSE FALSE FALSE FALSE
## 210 FALSE FALSE FALSE FALSE FALSE
## 211 FALSE FALSE FALSE FALSE FALSE
## 212 FALSE FALSE FALSE FALSE FALSE
## 213 FALSE FALSE FALSE FALSE FALSE
## 214 FALSE FALSE FALSE FALSE FALSE
## 215 FALSE FALSE FALSE FALSE FALSE
## 216 FALSE FALSE FALSE FALSE FALSE
## 217 FALSE FALSE FALSE FALSE FALSE
## 218 TRUE FALSE FALSE FALSE FALSE
## 219 FALSE FALSE FALSE FALSE FALSE
## 220 FALSE FALSE FALSE FALSE FALSE
## 221 FALSE FALSE FALSE FALSE FALSE
## 222 FALSE FALSE FALSE FALSE FALSE
## 223 FALSE FALSE FALSE FALSE FALSE
## 224 FALSE FALSE FALSE FALSE FALSE
## 225 FALSE FALSE FALSE FALSE FALSE
## 226 FALSE FALSE FALSE FALSE FALSE
## 227 FALSE FALSE FALSE FALSE FALSE
## 228 FALSE FALSE FALSE FALSE FALSE
## 229 FALSE FALSE FALSE FALSE FALSE
## 230 FALSE FALSE FALSE FALSE FALSE
## 231 FALSE FALSE FALSE FALSE FALSE
## 232 FALSE FALSE FALSE FALSE FALSE
## 233 FALSE FALSE FALSE FALSE FALSE
## 234 FALSE FALSE FALSE FALSE FALSE
## 235 FALSE FALSE FALSE FALSE FALSE
## 236 FALSE FALSE FALSE FALSE FALSE
## 237 FALSE FALSE FALSE FALSE FALSE
## 238 FALSE FALSE FALSE FALSE FALSE
## 239 FALSE FALSE FALSE FALSE FALSE
## 240 FALSE FALSE FALSE FALSE FALSE
## 241 FALSE FALSE FALSE FALSE FALSE
## 242 FALSE FALSE FALSE FALSE FALSE
## 243 FALSE FALSE FALSE FALSE FALSE
## 244 FALSE FALSE FALSE FALSE FALSE
## 245 FALSE FALSE FALSE FALSE FALSE
## 246 FALSE FALSE FALSE FALSE FALSE
## 247 FALSE FALSE FALSE FALSE FALSE
## 248 FALSE FALSE FALSE FALSE FALSE
## 249 FALSE FALSE FALSE FALSE FALSE
## 250 FALSE FALSE FALSE FALSE FALSE
## 251 FALSE FALSE FALSE FALSE FALSE
## 252 FALSE FALSE FALSE FALSE FALSE
## 253 FALSE FALSE FALSE FALSE FALSE
## 254 FALSE FALSE FALSE FALSE FALSE
## 255 FALSE FALSE FALSE FALSE FALSE
## 256 FALSE FALSE FALSE FALSE FALSE
## 257 FALSE FALSE FALSE FALSE FALSE
## 258 FALSE FALSE FALSE FALSE FALSE
## 259 FALSE FALSE FALSE FALSE FALSE
## 260 FALSE FALSE FALSE FALSE FALSE
## 261 FALSE FALSE FALSE FALSE FALSE
## 262 FALSE FALSE FALSE FALSE FALSE
## 263 FALSE FALSE FALSE FALSE FALSE
## 264 FALSE FALSE FALSE FALSE FALSE
## 265 FALSE FALSE FALSE FALSE FALSE
## 266 FALSE FALSE FALSE FALSE FALSE
## 267 FALSE FALSE FALSE FALSE FALSE
## 268 FALSE FALSE FALSE FALSE FALSE
## 269 FALSE FALSE FALSE FALSE FALSE
## 270 FALSE FALSE FALSE FALSE FALSE
## 271 FALSE FALSE FALSE FALSE FALSE
## 272 FALSE FALSE FALSE FALSE FALSE
## 273 FALSE FALSE FALSE FALSE FALSE
## 274 FALSE FALSE FALSE FALSE FALSE
## 275 FALSE FALSE FALSE FALSE FALSE
## 276 FALSE FALSE FALSE FALSE FALSE
## 277 FALSE FALSE FALSE FALSE FALSE
## 278 FALSE FALSE FALSE FALSE FALSE
## 279 FALSE FALSE FALSE FALSE FALSE
## 280 FALSE FALSE FALSE FALSE FALSE
## 281 FALSE FALSE FALSE FALSE FALSE
## 282 FALSE FALSE FALSE FALSE FALSE
## 283 FALSE FALSE FALSE FALSE FALSE
## 284 FALSE FALSE FALSE FALSE FALSE
## 285 FALSE FALSE FALSE FALSE FALSE
## 286 FALSE FALSE FALSE FALSE FALSE
## 287 FALSE FALSE FALSE FALSE FALSE
## 288 FALSE FALSE FALSE FALSE FALSE
## 289 FALSE FALSE FALSE FALSE FALSE
## 290 FALSE FALSE FALSE FALSE FALSE
## 291 FALSE FALSE FALSE FALSE FALSE
## 292 FALSE FALSE FALSE FALSE FALSE
## 293 FALSE FALSE FALSE FALSE FALSE
## 294 FALSE FALSE FALSE FALSE FALSE
## 295 FALSE FALSE FALSE FALSE FALSE
## 296 FALSE FALSE FALSE FALSE FALSE
## 297 FALSE FALSE FALSE FALSE FALSE
## 298 FALSE FALSE FALSE FALSE FALSE
## 299 FALSE FALSE FALSE FALSE FALSE
## 300 FALSE FALSE FALSE FALSE FALSE
## 301 FALSE FALSE FALSE FALSE FALSE
## 302 FALSE FALSE FALSE FALSE FALSE
## 303 FALSE FALSE FALSE FALSE FALSE
## 304 FALSE FALSE FALSE FALSE FALSE
## 305 FALSE FALSE FALSE FALSE FALSE
## 306 FALSE FALSE FALSE FALSE FALSE
## 307 FALSE FALSE FALSE FALSE FALSE
## 308 FALSE FALSE FALSE FALSE FALSE
## 309 FALSE FALSE FALSE FALSE FALSE
## 310 FALSE FALSE FALSE FALSE FALSE
## 311 FALSE FALSE FALSE FALSE FALSE
## 312 FALSE FALSE FALSE FALSE FALSE
## 313 FALSE FALSE FALSE FALSE FALSE
## 314 FALSE FALSE FALSE FALSE FALSE
## 315 FALSE FALSE FALSE FALSE FALSE
## 316 FALSE FALSE FALSE FALSE FALSE
## 317 FALSE FALSE FALSE FALSE FALSE
## 318 FALSE FALSE FALSE FALSE FALSE
## 319 FALSE FALSE FALSE FALSE FALSE
## 320 FALSE FALSE FALSE FALSE FALSE
## 321 FALSE FALSE FALSE FALSE FALSE
## 322 FALSE FALSE FALSE FALSE FALSE
## 323 FALSE FALSE FALSE FALSE FALSE
## 324 FALSE FALSE FALSE FALSE FALSE
## 325 FALSE FALSE FALSE FALSE FALSE
## 326 FALSE FALSE FALSE FALSE FALSE
## 327 FALSE FALSE FALSE FALSE FALSE
## 328 FALSE FALSE FALSE FALSE FALSE
## 329 FALSE FALSE FALSE FALSE FALSE
## 330 FALSE FALSE FALSE FALSE FALSE
## 331 FALSE FALSE FALSE FALSE FALSE
## 332 FALSE FALSE FALSE FALSE FALSE
## 333 FALSE FALSE FALSE FALSE FALSE
## 334 FALSE FALSE FALSE FALSE FALSE
## 335 FALSE FALSE FALSE FALSE FALSE
## 336 FALSE FALSE FALSE FALSE FALSE
## 337 FALSE FALSE FALSE FALSE FALSE
## 338 FALSE FALSE FALSE FALSE FALSE
## 339 FALSE FALSE FALSE FALSE FALSE
## 340 FALSE FALSE FALSE FALSE FALSE
## 341 FALSE FALSE FALSE FALSE FALSE
## 342 FALSE FALSE FALSE FALSE FALSE
## 343 FALSE FALSE FALSE FALSE FALSE
## 344 FALSE FALSE FALSE FALSE FALSE
## 345 FALSE FALSE FALSE FALSE FALSE
## 346 FALSE FALSE FALSE FALSE FALSE
## 347 FALSE FALSE FALSE FALSE FALSE
## 348 FALSE FALSE FALSE FALSE FALSE
## 349 FALSE FALSE FALSE FALSE FALSE
## 350 FALSE FALSE FALSE FALSE FALSE
## 351 FALSE FALSE FALSE FALSE FALSE
## 352 FALSE FALSE FALSE FALSE TRUE
## 353 FALSE FALSE FALSE FALSE FALSE
## 354 FALSE FALSE FALSE FALSE FALSE
## 355 FALSE FALSE FALSE FALSE FALSE
## 356 FALSE FALSE FALSE FALSE FALSE
## 357 FALSE FALSE FALSE FALSE FALSE
## 358 FALSE FALSE FALSE FALSE FALSE
## 359 FALSE FALSE FALSE FALSE FALSE
## 360 FALSE FALSE FALSE FALSE FALSE
## 361 FALSE FALSE FALSE FALSE FALSE
## 362 FALSE FALSE FALSE FALSE FALSE
## 363 FALSE FALSE FALSE FALSE FALSE
## 364 FALSE FALSE FALSE FALSE FALSE
## 365 FALSE FALSE FALSE FALSE FALSE
## 366 FALSE FALSE FALSE TRUE FALSE
## 367 FALSE FALSE FALSE FALSE FALSE
## 368 FALSE FALSE FALSE FALSE FALSE
## 369 FALSE FALSE FALSE FALSE FALSE
## 370 FALSE FALSE FALSE FALSE FALSE
## 371 FALSE FALSE FALSE FALSE FALSE
## 372 FALSE FALSE FALSE FALSE FALSE
## 373 FALSE FALSE FALSE FALSE FALSE
## 374 FALSE FALSE FALSE FALSE FALSE
## 375 FALSE FALSE FALSE FALSE FALSE
## 376 FALSE FALSE FALSE FALSE FALSE
## 377 FALSE FALSE FALSE FALSE FALSE
## 378 FALSE FALSE FALSE FALSE FALSE
## 379 FALSE FALSE FALSE FALSE FALSE
## 380 FALSE FALSE FALSE FALSE FALSE
## 381 FALSE FALSE FALSE FALSE FALSE
## 382 FALSE FALSE FALSE FALSE FALSE
## 383 FALSE FALSE FALSE FALSE FALSE
## 384 FALSE FALSE FALSE FALSE FALSE
## 385 FALSE FALSE FALSE FALSE FALSE
## 386 FALSE FALSE FALSE FALSE FALSE
## 387 TRUE FALSE FALSE FALSE FALSE
## 388 FALSE FALSE FALSE FALSE FALSE
## 389 FALSE FALSE FALSE FALSE FALSE
## 390 FALSE FALSE FALSE FALSE FALSE
## 391 FALSE FALSE FALSE FALSE FALSE
## 392 FALSE FALSE FALSE FALSE FALSE
## 393 FALSE FALSE FALSE FALSE FALSE
## 394 FALSE FALSE FALSE FALSE FALSE
## 395 FALSE FALSE FALSE FALSE FALSE
## 396 FALSE FALSE FALSE FALSE FALSE
## 397 FALSE FALSE FALSE FALSE FALSE
## 398 FALSE FALSE FALSE FALSE FALSE
## 399 FALSE FALSE FALSE FALSE FALSE
## 400 FALSE FALSE FALSE FALSE FALSE
## 401 FALSE FALSE FALSE FALSE FALSE
## 402 FALSE FALSE FALSE FALSE FALSE
## 403 FALSE FALSE FALSE FALSE FALSE
## 404 FALSE FALSE FALSE FALSE FALSE
## 405 FALSE FALSE FALSE FALSE FALSE
## 406 FALSE FALSE FALSE FALSE FALSE
## 407 FALSE FALSE FALSE FALSE FALSE
## 408 FALSE FALSE FALSE FALSE FALSE
## 409 FALSE FALSE FALSE FALSE FALSE
## 410 FALSE FALSE FALSE FALSE FALSE
## 411 FALSE FALSE FALSE FALSE FALSE
## 412 FALSE FALSE FALSE FALSE FALSE
## 413 FALSE FALSE FALSE FALSE FALSE
## 414 FALSE FALSE FALSE FALSE FALSE
## 415 FALSE FALSE FALSE FALSE FALSE
## 416 FALSE FALSE FALSE FALSE FALSE
## 417 FALSE FALSE FALSE FALSE FALSE
## 418 FALSE FALSE FALSE FALSE FALSE
## 419 FALSE FALSE FALSE FALSE FALSE
## 420 FALSE FALSE FALSE FALSE FALSE
## 421 FALSE FALSE FALSE FALSE FALSE
## 422 FALSE FALSE FALSE FALSE FALSE
## 423 FALSE FALSE FALSE FALSE FALSE
## 424 FALSE FALSE FALSE FALSE FALSE
## 425 FALSE FALSE FALSE FALSE FALSE
## 426 FALSE FALSE FALSE FALSE FALSE
## 427 FALSE FALSE FALSE FALSE FALSE
## 428 FALSE FALSE FALSE FALSE FALSE
## 429 FALSE FALSE FALSE FALSE FALSE
## 430 FALSE FALSE FALSE FALSE FALSE
## 431 FALSE FALSE FALSE FALSE FALSE
## 432 FALSE FALSE FALSE FALSE FALSE
## 433 FALSE FALSE FALSE FALSE FALSE
## 434 FALSE FALSE FALSE FALSE FALSE
## 435 FALSE FALSE FALSE FALSE FALSE
## 436 FALSE FALSE FALSE FALSE FALSE
## 437 FALSE FALSE FALSE FALSE FALSE
## 438 FALSE FALSE FALSE FALSE FALSE
## 439 FALSE FALSE FALSE FALSE FALSE
## 440 FALSE FALSE FALSE FALSE FALSE
## 441 FALSE FALSE FALSE FALSE FALSE
## 442 FALSE FALSE FALSE FALSE FALSE
## 443 FALSE FALSE FALSE FALSE FALSE
## 444 FALSE FALSE FALSE FALSE FALSE
## 445 FALSE FALSE FALSE FALSE FALSE
## 446 FALSE FALSE FALSE FALSE FALSE
## 447 FALSE FALSE FALSE FALSE FALSE
## 448 FALSE FALSE FALSE FALSE FALSE
## 449 FALSE FALSE FALSE FALSE TRUE
## 450 FALSE FALSE FALSE FALSE FALSE
## 451 FALSE FALSE FALSE FALSE FALSE
## 452 FALSE FALSE FALSE FALSE FALSE
## 453 FALSE FALSE FALSE FALSE FALSE
## 454 FALSE FALSE FALSE FALSE FALSE
## 455 FALSE FALSE FALSE FALSE FALSE
## 456 FALSE FALSE FALSE FALSE FALSE
## 457 FALSE FALSE FALSE FALSE FALSE
## 458 FALSE FALSE FALSE FALSE FALSE
## 459 FALSE FALSE FALSE FALSE FALSE
## 460 FALSE FALSE FALSE FALSE FALSE
## 461 FALSE FALSE FALSE FALSE FALSE
## 462 FALSE FALSE FALSE FALSE FALSE
## 463 FALSE FALSE FALSE FALSE FALSE
## 464 FALSE FALSE FALSE FALSE FALSE
## 465 FALSE FALSE FALSE FALSE FALSE
## 466 FALSE FALSE FALSE FALSE FALSE
## 467 FALSE FALSE FALSE FALSE FALSE
## 468 FALSE FALSE FALSE FALSE FALSE
## 469 FALSE FALSE FALSE FALSE FALSE
## 470 FALSE FALSE FALSE FALSE FALSE
## 471 FALSE FALSE FALSE FALSE FALSE
## 472 FALSE FALSE FALSE FALSE FALSE
## 473 FALSE FALSE FALSE FALSE FALSE
## 474 FALSE FALSE FALSE FALSE FALSE
## 475 FALSE FALSE FALSE FALSE FALSE
## 476 FALSE FALSE FALSE FALSE FALSE
## 477 FALSE FALSE FALSE FALSE FALSE
## 478 FALSE FALSE FALSE FALSE FALSE
## 479 FALSE FALSE FALSE FALSE FALSE
## 480 FALSE FALSE FALSE FALSE FALSE
## 481 FALSE FALSE FALSE FALSE FALSE
## 482 FALSE FALSE FALSE FALSE FALSE
## 483 FALSE FALSE FALSE FALSE FALSE
## 484 FALSE FALSE FALSE FALSE FALSE
## 485 FALSE FALSE FALSE FALSE FALSE
## 486 FALSE FALSE FALSE FALSE FALSE
## 487 FALSE FALSE FALSE FALSE FALSE
## 488 FALSE FALSE FALSE FALSE FALSE
## 489 FALSE FALSE FALSE FALSE FALSE
## 490 FALSE FALSE FALSE FALSE FALSE
## 491 FALSE FALSE FALSE FALSE FALSE
## 492 FALSE FALSE FALSE FALSE FALSE
## 493 FALSE FALSE FALSE FALSE FALSE
## 494 FALSE FALSE FALSE FALSE FALSE
## 495 FALSE FALSE FALSE FALSE FALSE
## 496 FALSE FALSE FALSE FALSE FALSE
## 497 FALSE FALSE FALSE FALSE FALSE
## 498 FALSE FALSE FALSE FALSE FALSE
## 499 FALSE FALSE FALSE FALSE FALSE
## 500 FALSE FALSE FALSE FALSE FALSE
## 501 FALSE FALSE FALSE FALSE FALSE
## 502 FALSE FALSE FALSE FALSE FALSE
## 503 FALSE FALSE FALSE FALSE FALSE
## 504 FALSE FALSE FALSE FALSE FALSE
## 505 FALSE FALSE FALSE FALSE FALSE
## 506 FALSE FALSE FALSE FALSE FALSE
## 507 FALSE FALSE FALSE FALSE FALSE
## 508 FALSE FALSE FALSE FALSE FALSE
## 509 FALSE FALSE FALSE FALSE FALSE
## 510 FALSE FALSE FALSE FALSE FALSE
## 511 FALSE FALSE FALSE FALSE FALSE
## 512 FALSE FALSE FALSE FALSE TRUE
## 513 FALSE FALSE FALSE FALSE FALSE
## 514 FALSE FALSE FALSE FALSE FALSE
## 515 FALSE FALSE FALSE FALSE FALSE
## 516 FALSE FALSE FALSE FALSE FALSE
## 517 FALSE FALSE FALSE FALSE FALSE
## 518 FALSE FALSE FALSE FALSE FALSE
## 519 FALSE FALSE FALSE FALSE FALSE
## 520 FALSE FALSE FALSE FALSE FALSE
## 521 FALSE FALSE FALSE FALSE FALSE
## 522 FALSE FALSE FALSE FALSE FALSE
## 523 FALSE FALSE FALSE FALSE FALSE
## 524 FALSE FALSE FALSE FALSE FALSE
## 525 FALSE FALSE FALSE FALSE FALSE
## 526 FALSE FALSE FALSE FALSE FALSE
## 527 FALSE FALSE FALSE FALSE FALSE
## 528 FALSE FALSE FALSE FALSE FALSE
## 529 FALSE FALSE FALSE FALSE FALSE
## 530 FALSE FALSE FALSE FALSE FALSE
## 531 FALSE FALSE FALSE FALSE FALSE
## 532 FALSE FALSE FALSE FALSE FALSE
## 533 FALSE FALSE FALSE FALSE FALSE
## 534 FALSE FALSE FALSE FALSE FALSE
## 535 FALSE FALSE FALSE FALSE FALSE
## 536 FALSE FALSE FALSE FALSE FALSE
## 537 FALSE FALSE FALSE FALSE FALSE
## 538 FALSE FALSE FALSE FALSE FALSE
## 539 FALSE FALSE FALSE FALSE FALSE
## 540 FALSE FALSE FALSE FALSE FALSE
## 541 FALSE FALSE FALSE FALSE FALSE
## 542 FALSE FALSE FALSE FALSE FALSE
## 543 FALSE FALSE FALSE FALSE FALSE
## 544 FALSE FALSE FALSE FALSE FALSE
## 545 FALSE FALSE FALSE FALSE FALSE
## 546 FALSE FALSE FALSE FALSE FALSE
## 547 FALSE FALSE FALSE FALSE FALSE
## 548 FALSE FALSE FALSE FALSE FALSE
## 549 FALSE FALSE FALSE FALSE FALSE
## 550 TRUE FALSE FALSE FALSE FALSE
## 551 FALSE FALSE FALSE FALSE FALSE
## 552 FALSE FALSE FALSE FALSE FALSE
## 553 FALSE FALSE FALSE FALSE FALSE
## 554 FALSE FALSE FALSE FALSE FALSE
## 555 FALSE FALSE FALSE FALSE FALSE
## 556 FALSE FALSE FALSE FALSE FALSE
## 557 FALSE FALSE FALSE FALSE FALSE
## 558 FALSE FALSE FALSE FALSE FALSE
## 559 FALSE FALSE FALSE FALSE FALSE
## 560 FALSE FALSE FALSE FALSE FALSE
## 561 FALSE FALSE FALSE FALSE FALSE
## 562 FALSE FALSE FALSE FALSE TRUE
## 563 FALSE FALSE FALSE FALSE FALSE
## 564 FALSE FALSE FALSE FALSE FALSE
## 565 FALSE FALSE FALSE FALSE FALSE
## 566 FALSE FALSE FALSE FALSE FALSE
## 567 FALSE FALSE FALSE FALSE FALSE
## 568 FALSE FALSE FALSE FALSE FALSE
## 569 FALSE FALSE FALSE FALSE FALSE
## 570 FALSE FALSE FALSE FALSE FALSE
## 571 FALSE FALSE FALSE FALSE FALSE
## 572 FALSE FALSE FALSE FALSE FALSE
## 573 FALSE FALSE FALSE FALSE FALSE
## 574 FALSE FALSE FALSE FALSE FALSE
## 575 FALSE FALSE FALSE FALSE FALSE
## 576 FALSE FALSE FALSE FALSE FALSE
## 577 FALSE FALSE FALSE FALSE FALSE
## 578 FALSE FALSE FALSE FALSE FALSE
## 579 FALSE FALSE FALSE FALSE FALSE
## 580 FALSE FALSE FALSE FALSE FALSE
## 581 FALSE FALSE FALSE FALSE FALSE
## 582 FALSE FALSE FALSE FALSE FALSE
## 583 FALSE FALSE FALSE FALSE FALSE
## 584 FALSE FALSE FALSE FALSE FALSE
## 585 FALSE FALSE FALSE FALSE FALSE
## 586 FALSE FALSE FALSE FALSE FALSE
## 587 FALSE FALSE FALSE FALSE FALSE
## 588 FALSE FALSE FALSE FALSE FALSE
## 589 FALSE FALSE FALSE FALSE FALSE
## 590 FALSE FALSE FALSE FALSE FALSE
## 591 FALSE FALSE FALSE FALSE FALSE
## 592 FALSE FALSE FALSE FALSE FALSE
## 593 FALSE FALSE FALSE FALSE FALSE
## 594 FALSE FALSE FALSE FALSE FALSE
## 595 FALSE FALSE FALSE FALSE FALSE
## 596 FALSE FALSE FALSE FALSE FALSE
## 597 FALSE FALSE FALSE FALSE FALSE
## 598 FALSE FALSE FALSE FALSE FALSE
## 599 FALSE FALSE FALSE FALSE FALSE
## 600 FALSE FALSE FALSE FALSE FALSE
## 601 FALSE FALSE FALSE FALSE FALSE
## 602 FALSE FALSE FALSE FALSE FALSE
## 603 FALSE FALSE FALSE FALSE FALSE
## 604 FALSE FALSE FALSE FALSE FALSE
## 605 FALSE FALSE FALSE FALSE FALSE
## 606 FALSE FALSE FALSE FALSE FALSE
## 607 FALSE FALSE FALSE FALSE FALSE
## 608 FALSE FALSE FALSE FALSE FALSE
## 609 FALSE FALSE FALSE FALSE FALSE
## 610 FALSE FALSE FALSE FALSE FALSE
## 611 FALSE FALSE FALSE FALSE FALSE
## 612 FALSE FALSE FALSE FALSE FALSE
## 613 FALSE FALSE FALSE FALSE FALSE
## 614 FALSE FALSE FALSE FALSE FALSE
## 615 FALSE FALSE FALSE FALSE FALSE
## 616 FALSE FALSE FALSE FALSE TRUE
## 617 FALSE FALSE FALSE FALSE FALSE
## 618 FALSE FALSE FALSE FALSE FALSE
## 619 FALSE FALSE FALSE FALSE FALSE
## 620 FALSE FALSE FALSE FALSE FALSE
## 621 FALSE FALSE FALSE FALSE FALSE
## 622 FALSE FALSE FALSE FALSE FALSE
## 623 FALSE FALSE FALSE FALSE FALSE
## 624 FALSE FALSE FALSE FALSE FALSE
## 625 FALSE FALSE FALSE FALSE FALSE
## 626 FALSE FALSE FALSE FALSE FALSE
## 627 FALSE FALSE FALSE FALSE FALSE
## 628 FALSE FALSE FALSE FALSE FALSE
## 629 FALSE FALSE FALSE FALSE FALSE
## 630 FALSE FALSE FALSE FALSE FALSE
## 631 FALSE FALSE FALSE FALSE FALSE
## 632 FALSE FALSE FALSE FALSE FALSE
## 633 FALSE FALSE FALSE FALSE FALSE
## 634 FALSE FALSE FALSE FALSE FALSE
## 635 FALSE FALSE FALSE FALSE FALSE
## 636 FALSE FALSE FALSE FALSE FALSE
## 637 FALSE FALSE FALSE FALSE FALSE
## 638 FALSE FALSE FALSE FALSE FALSE
## 639 TRUE FALSE FALSE FALSE FALSE
## 640 FALSE FALSE FALSE FALSE FALSE
## 641 FALSE FALSE FALSE FALSE FALSE
## 642 FALSE FALSE FALSE FALSE FALSE
## 643 FALSE FALSE FALSE FALSE FALSE
## 644 FALSE FALSE FALSE FALSE FALSE
## 645 FALSE FALSE FALSE FALSE FALSE
## 646 FALSE FALSE FALSE FALSE FALSE
## 647 FALSE FALSE FALSE TRUE FALSE
## 648 FALSE FALSE FALSE FALSE FALSE
## 649 FALSE FALSE FALSE FALSE FALSE
## 650 FALSE FALSE FALSE FALSE FALSE
## 651 FALSE FALSE FALSE FALSE FALSE
## 652 FALSE FALSE FALSE FALSE FALSE
## 653 FALSE FALSE FALSE FALSE FALSE
## 654 FALSE FALSE FALSE FALSE FALSE
## 655 FALSE FALSE FALSE FALSE FALSE
## 656 FALSE FALSE FALSE FALSE FALSE
## 657 FALSE FALSE FALSE FALSE FALSE
## 658 FALSE FALSE FALSE FALSE FALSE
## 659 FALSE FALSE FALSE FALSE FALSE
## 660 FALSE FALSE FALSE FALSE FALSE
## 661 FALSE FALSE FALSE FALSE FALSE
## 662 FALSE FALSE FALSE FALSE FALSE
## 663 FALSE FALSE FALSE FALSE FALSE
## 664 FALSE FALSE FALSE FALSE FALSE
## 665 FALSE FALSE FALSE FALSE FALSE
## 666 FALSE FALSE FALSE FALSE FALSE
## 667 FALSE FALSE FALSE FALSE FALSE
## 668 FALSE FALSE FALSE FALSE FALSE
## 669 FALSE FALSE FALSE FALSE FALSE
## 670 FALSE FALSE FALSE FALSE FALSE
## 671 FALSE FALSE FALSE FALSE FALSE
## 672 FALSE FALSE FALSE FALSE FALSE
## 673 FALSE FALSE FALSE FALSE FALSE
## 674 FALSE FALSE FALSE FALSE FALSE
## 675 FALSE FALSE FALSE FALSE FALSE
## 676 FALSE FALSE FALSE FALSE FALSE
## 677 FALSE FALSE FALSE FALSE FALSE
## 678 FALSE FALSE FALSE FALSE FALSE
## 679 FALSE FALSE FALSE FALSE FALSE
## 680 FALSE FALSE FALSE FALSE FALSE
## 681 FALSE FALSE FALSE FALSE FALSE
## 682 FALSE FALSE FALSE FALSE FALSE
## 683 FALSE FALSE FALSE FALSE FALSE
## 684 FALSE FALSE FALSE FALSE FALSE
## 685 FALSE FALSE FALSE FALSE FALSE
## 686 FALSE FALSE FALSE FALSE FALSE
## 687 FALSE FALSE FALSE FALSE FALSE
## 688 FALSE FALSE FALSE FALSE FALSE
## 689 TRUE FALSE FALSE FALSE FALSE
## 690 FALSE FALSE FALSE FALSE FALSE
## 691 FALSE FALSE FALSE FALSE FALSE
## 692 FALSE FALSE FALSE FALSE FALSE
## 693 FALSE FALSE FALSE FALSE FALSE
## 694 FALSE FALSE FALSE FALSE FALSE
## 695 FALSE FALSE FALSE FALSE FALSE
## 696 FALSE FALSE FALSE FALSE FALSE
## 697 FALSE FALSE FALSE FALSE FALSE
## 698 FALSE FALSE FALSE FALSE FALSE
## 699 FALSE FALSE FALSE FALSE FALSE
## 700 FALSE FALSE FALSE FALSE FALSE
## 701 FALSE FALSE FALSE FALSE FALSE
## 702 FALSE FALSE FALSE FALSE FALSE
## 703 FALSE FALSE FALSE FALSE FALSE
## 704 FALSE FALSE FALSE FALSE FALSE
## 705 FALSE FALSE FALSE FALSE FALSE
## 706 FALSE FALSE FALSE FALSE FALSE
## 707 FALSE FALSE FALSE FALSE FALSE
## 708 FALSE FALSE FALSE FALSE FALSE
## 709 FALSE FALSE FALSE FALSE FALSE
## 710 FALSE FALSE FALSE FALSE FALSE
## 711 FALSE FALSE FALSE FALSE FALSE
## 712 FALSE FALSE FALSE FALSE FALSE
## 713 FALSE FALSE FALSE FALSE FALSE
## 714 FALSE FALSE FALSE FALSE FALSE
## 715 FALSE FALSE FALSE FALSE FALSE
## 716 FALSE FALSE FALSE FALSE FALSE
## 717 FALSE FALSE FALSE FALSE FALSE
## 718 FALSE FALSE FALSE FALSE FALSE
## 719 FALSE FALSE FALSE FALSE FALSE
## 720 FALSE FALSE FALSE FALSE FALSE
## 721 FALSE FALSE FALSE FALSE FALSE
## 722 FALSE FALSE FALSE FALSE FALSE
## 723 FALSE FALSE FALSE FALSE FALSE
## 724 FALSE FALSE FALSE FALSE FALSE
## 725 FALSE FALSE FALSE FALSE FALSE
## 726 FALSE FALSE FALSE FALSE FALSE
## 727 FALSE FALSE FALSE FALSE FALSE
## 728 FALSE FALSE FALSE FALSE FALSE
## 729 FALSE FALSE FALSE FALSE FALSE
## 730 FALSE FALSE FALSE FALSE FALSE
## 731 FALSE FALSE FALSE FALSE FALSE
## 732 FALSE FALSE FALSE FALSE FALSE
## 733 FALSE FALSE FALSE FALSE FALSE
## 734 FALSE FALSE FALSE FALSE FALSE
## 735 FALSE FALSE FALSE FALSE FALSE
## 736 FALSE FALSE FALSE FALSE FALSE
## 737 FALSE FALSE FALSE FALSE FALSE
## 738 FALSE FALSE FALSE FALSE FALSE
## 739 FALSE FALSE FALSE FALSE FALSE
## 740 FALSE FALSE FALSE FALSE FALSE
## 741 FALSE FALSE FALSE FALSE FALSE
## 742 FALSE FALSE FALSE FALSE FALSE
## 743 FALSE FALSE FALSE FALSE FALSE
## 744 FALSE FALSE FALSE FALSE FALSE
## 745 FALSE FALSE FALSE FALSE FALSE
## 746 FALSE FALSE FALSE FALSE FALSE
## 747 FALSE FALSE FALSE FALSE FALSE
## 748 FALSE FALSE FALSE FALSE FALSE
## 749 FALSE FALSE FALSE FALSE FALSE
## 750 FALSE FALSE FALSE FALSE FALSE
## 751 FALSE FALSE FALSE FALSE FALSE
## 752 FALSE FALSE FALSE FALSE FALSE
## 753 FALSE FALSE FALSE FALSE FALSE
## 754 FALSE FALSE FALSE FALSE FALSE
## 755 FALSE FALSE FALSE FALSE FALSE
## 756 FALSE FALSE FALSE FALSE FALSE
## 757 FALSE FALSE FALSE FALSE FALSE
## 758 FALSE FALSE FALSE FALSE FALSE
## 759 FALSE FALSE FALSE FALSE FALSE
## 760 FALSE FALSE FALSE FALSE FALSE
## 761 FALSE FALSE FALSE FALSE FALSE
## 762 FALSE FALSE FALSE FALSE FALSE
## 763 FALSE FALSE FALSE FALSE FALSE
## 764 FALSE FALSE FALSE FALSE FALSE
## 765 FALSE FALSE FALSE FALSE FALSE
## 766 FALSE FALSE FALSE FALSE FALSE
## 767 FALSE FALSE FALSE FALSE FALSE
## 768 FALSE FALSE FALSE FALSE FALSE
## 769 FALSE FALSE FALSE FALSE FALSE
## 770 FALSE FALSE FALSE FALSE FALSE
## 771 FALSE FALSE FALSE FALSE FALSE
## 772 FALSE FALSE FALSE FALSE FALSE
## 773 FALSE FALSE FALSE FALSE FALSE
## 774 FALSE FALSE FALSE FALSE FALSE
## 775 FALSE FALSE FALSE FALSE FALSE
## 776 FALSE FALSE FALSE FALSE FALSE
## 777 FALSE FALSE FALSE FALSE FALSE
## 778 FALSE FALSE FALSE FALSE FALSE
## 779 FALSE FALSE FALSE FALSE FALSE
## 780 FALSE FALSE FALSE FALSE FALSE
## 781 FALSE FALSE FALSE FALSE FALSE
## 782 FALSE FALSE FALSE FALSE FALSE
## 783 FALSE FALSE FALSE FALSE FALSE
## 784 FALSE FALSE FALSE FALSE FALSE
## 785 FALSE FALSE FALSE FALSE FALSE
## 786 FALSE FALSE FALSE FALSE FALSE
## 787 FALSE FALSE FALSE FALSE FALSE
## 788 FALSE FALSE FALSE FALSE FALSE
## 789 FALSE FALSE FALSE FALSE FALSE
## 790 FALSE FALSE FALSE FALSE FALSE
## 791 FALSE FALSE FALSE FALSE FALSE
## 792 FALSE FALSE FALSE FALSE FALSE
## 793 FALSE FALSE FALSE FALSE FALSE
## 794 FALSE FALSE FALSE FALSE FALSE
## 795 FALSE FALSE FALSE FALSE FALSE
## 796 FALSE FALSE FALSE FALSE FALSE
## 797 FALSE FALSE FALSE FALSE FALSE
## 798 FALSE FALSE FALSE FALSE FALSE
## 799 FALSE FALSE FALSE FALSE FALSE
## 800 FALSE FALSE FALSE FALSE FALSE
## 801 FALSE FALSE FALSE FALSE FALSE
## 802 FALSE FALSE FALSE FALSE FALSE
## 803 FALSE FALSE FALSE FALSE FALSE
## 804 FALSE FALSE FALSE FALSE FALSE
## 805 FALSE FALSE FALSE FALSE FALSE
## 806 TRUE FALSE FALSE FALSE FALSE
## 807 FALSE FALSE FALSE FALSE FALSE
## 808 FALSE FALSE FALSE FALSE FALSE
## 809 FALSE FALSE FALSE FALSE FALSE
## 810 FALSE FALSE FALSE FALSE FALSE
## 811 FALSE FALSE FALSE FALSE FALSE
## 812 FALSE FALSE FALSE FALSE FALSE
## 813 FALSE FALSE FALSE FALSE FALSE
## 814 FALSE FALSE FALSE FALSE FALSE
## 815 FALSE FALSE FALSE FALSE FALSE
## 816 FALSE FALSE FALSE FALSE FALSE
## 817 FALSE FALSE FALSE FALSE FALSE
## 818 FALSE FALSE FALSE FALSE FALSE
## 819 FALSE FALSE FALSE FALSE FALSE
## 820 FALSE FALSE FALSE FALSE FALSE
## 821 FALSE FALSE FALSE FALSE FALSE
## 822 FALSE FALSE FALSE FALSE FALSE
## 823 FALSE FALSE FALSE FALSE FALSE
## 824 FALSE FALSE FALSE FALSE FALSE
## 825 FALSE FALSE FALSE FALSE FALSE
## 826 FALSE FALSE FALSE FALSE FALSE
## 827 FALSE FALSE FALSE FALSE FALSE
## 828 FALSE FALSE FALSE FALSE FALSE
## 829 FALSE FALSE FALSE FALSE FALSE
## 830 FALSE FALSE FALSE FALSE FALSE
## 831 FALSE FALSE FALSE FALSE FALSE
## 832 FALSE FALSE FALSE FALSE FALSE
## 833 FALSE FALSE FALSE FALSE FALSE
## 834 FALSE FALSE FALSE FALSE FALSE
## 835 FALSE FALSE FALSE FALSE FALSE
## 836 FALSE FALSE FALSE FALSE FALSE
## 837 FALSE FALSE FALSE FALSE FALSE
## 838 FALSE FALSE FALSE FALSE FALSE
## 839 FALSE FALSE FALSE FALSE FALSE
## 840 FALSE FALSE FALSE FALSE FALSE
## 841 FALSE FALSE FALSE FALSE FALSE
## 842 FALSE FALSE FALSE FALSE FALSE
## 843 FALSE FALSE FALSE FALSE FALSE
## 844 FALSE FALSE FALSE FALSE FALSE
## 845 FALSE FALSE FALSE FALSE FALSE
## 846 FALSE FALSE FALSE FALSE FALSE
## 847 FALSE FALSE FALSE FALSE FALSE
## 848 FALSE FALSE FALSE FALSE FALSE
## 849 FALSE FALSE FALSE FALSE FALSE
## 850 FALSE FALSE FALSE FALSE FALSE
## 851 FALSE FALSE FALSE FALSE FALSE
## 852 FALSE FALSE FALSE FALSE FALSE
## 853 FALSE FALSE FALSE FALSE FALSE
## 854 FALSE FALSE FALSE FALSE FALSE
## 855 FALSE FALSE FALSE FALSE FALSE
## 856 FALSE FALSE FALSE FALSE FALSE
## 857 FALSE FALSE FALSE FALSE FALSE
## 858 FALSE FALSE FALSE FALSE FALSE
## 859 FALSE FALSE FALSE FALSE FALSE
## 860 FALSE FALSE FALSE FALSE FALSE
## 861 FALSE FALSE FALSE FALSE FALSE
## 862 FALSE FALSE FALSE FALSE FALSE
## 863 FALSE FALSE FALSE FALSE FALSE
## 864 FALSE FALSE FALSE FALSE FALSE
## 865 FALSE FALSE FALSE FALSE FALSE
## 866 FALSE FALSE FALSE FALSE FALSE
## 867 FALSE FALSE FALSE FALSE FALSE
## 868 FALSE FALSE FALSE FALSE FALSE
## 869 FALSE FALSE FALSE FALSE FALSE
## 870 FALSE FALSE FALSE FALSE FALSE
## 871 FALSE FALSE FALSE FALSE FALSE
## 872 FALSE FALSE FALSE FALSE FALSE
## 873 FALSE FALSE FALSE FALSE FALSE
## 874 FALSE FALSE FALSE FALSE FALSE
## 875 FALSE FALSE FALSE FALSE FALSE
## 876 FALSE FALSE FALSE FALSE FALSE
## 877 FALSE FALSE FALSE FALSE FALSE
## 878 FALSE FALSE FALSE FALSE FALSE
## 879 FALSE FALSE FALSE FALSE FALSE
## 880 FALSE FALSE FALSE FALSE FALSE
## 881 FALSE FALSE FALSE FALSE FALSE
## 882 FALSE FALSE FALSE FALSE FALSE
## 883 FALSE FALSE FALSE FALSE FALSE
## 884 FALSE FALSE FALSE FALSE FALSE
## 885 FALSE FALSE FALSE FALSE FALSE
## 886 FALSE FALSE FALSE FALSE FALSE
## 887 FALSE FALSE FALSE FALSE FALSE
## 888 FALSE FALSE FALSE FALSE FALSE
## 889 FALSE FALSE FALSE FALSE FALSE
## 890 FALSE FALSE FALSE FALSE FALSE
## 891 FALSE FALSE FALSE FALSE FALSE
## 892 FALSE FALSE FALSE FALSE FALSE
## 893 FALSE FALSE FALSE FALSE FALSE
## 894 FALSE FALSE FALSE FALSE FALSE
## 895 FALSE FALSE FALSE FALSE FALSE
## 896 FALSE FALSE FALSE FALSE FALSE
## 897 FALSE FALSE FALSE FALSE FALSE
## 898 FALSE FALSE FALSE FALSE FALSE
## 899 FALSE FALSE FALSE FALSE FALSE
## 900 FALSE FALSE FALSE FALSE FALSE
## 901 FALSE FALSE FALSE FALSE FALSE
## 902 FALSE FALSE FALSE FALSE FALSE
## 903 FALSE FALSE FALSE FALSE FALSE
## 904 FALSE FALSE FALSE FALSE FALSE
## 905 FALSE FALSE FALSE FALSE FALSE
## 906 FALSE FALSE FALSE FALSE FALSE
## 907 FALSE FALSE FALSE FALSE FALSE
## 908 FALSE FALSE FALSE FALSE FALSE
## 909 FALSE FALSE FALSE FALSE FALSE
## 910 FALSE FALSE FALSE FALSE FALSE
## 911 FALSE FALSE FALSE FALSE FALSE
## 912 FALSE FALSE FALSE FALSE FALSE
## 913 FALSE FALSE FALSE FALSE FALSE
## 914 FALSE FALSE FALSE FALSE FALSE
## 915 FALSE FALSE FALSE FALSE FALSE
## 916 FALSE FALSE FALSE FALSE FALSE
## 917 FALSE FALSE FALSE FALSE FALSE
## 918 FALSE FALSE FALSE FALSE FALSE
## 919 FALSE FALSE FALSE FALSE FALSE
## 920 FALSE FALSE FALSE FALSE FALSE
## 921 FALSE FALSE FALSE FALSE FALSE
## 922 FALSE FALSE FALSE FALSE FALSE
## 923 FALSE FALSE FALSE FALSE FALSE
## 924 FALSE FALSE FALSE FALSE FALSE
## 925 FALSE FALSE FALSE FALSE FALSE
## 926 FALSE FALSE FALSE FALSE FALSE
## 927 FALSE FALSE FALSE FALSE FALSE
## 928 FALSE FALSE FALSE FALSE FALSE
## 929 FALSE FALSE FALSE FALSE FALSE
## 930 FALSE FALSE FALSE FALSE FALSE
## 931 FALSE FALSE FALSE FALSE FALSE
## 932 FALSE FALSE FALSE FALSE FALSE
## 933 FALSE FALSE FALSE FALSE FALSE
## 934 FALSE FALSE FALSE FALSE TRUE
## 935 FALSE FALSE FALSE FALSE FALSE
## 936 FALSE FALSE FALSE FALSE FALSE
## 937 FALSE FALSE FALSE FALSE FALSE
## 938 FALSE FALSE FALSE FALSE FALSE
## 939 FALSE FALSE FALSE FALSE FALSE
## 940 FALSE FALSE FALSE FALSE FALSE
## 941 FALSE FALSE FALSE FALSE FALSE
## 942 FALSE FALSE FALSE FALSE FALSE
## 943 FALSE FALSE FALSE FALSE FALSE
## 944 FALSE FALSE FALSE TRUE FALSE
## 945 FALSE FALSE FALSE FALSE FALSE
## 946 FALSE FALSE FALSE FALSE FALSE
## 947 FALSE FALSE FALSE FALSE FALSE
## 948 FALSE FALSE FALSE FALSE FALSE
## 949 FALSE FALSE FALSE FALSE FALSE
## 950 FALSE FALSE FALSE FALSE FALSE
## 951 FALSE FALSE FALSE FALSE FALSE
## 952 FALSE FALSE FALSE FALSE FALSE
## 953 FALSE FALSE FALSE FALSE FALSE
## 954 FALSE FALSE FALSE FALSE FALSE
## 955 FALSE FALSE FALSE FALSE FALSE
## 956 FALSE FALSE FALSE FALSE FALSE
## 957 FALSE FALSE FALSE FALSE FALSE
## 958 FALSE FALSE FALSE FALSE FALSE
## 959 FALSE FALSE FALSE FALSE FALSE
## 960 FALSE FALSE FALSE FALSE FALSE
## 961 TRUE FALSE FALSE FALSE FALSE
## 962 FALSE FALSE FALSE FALSE FALSE
## 963 FALSE FALSE FALSE FALSE FALSE
## 964 FALSE FALSE FALSE FALSE FALSE
## 965 FALSE FALSE FALSE FALSE FALSE
## 966 FALSE FALSE FALSE FALSE FALSE
## 967 FALSE FALSE FALSE FALSE FALSE
## 968 FALSE FALSE FALSE FALSE FALSE
## 969 FALSE FALSE FALSE FALSE FALSE
## 970 FALSE FALSE FALSE FALSE FALSE
## 971 FALSE FALSE FALSE FALSE FALSE
## 972 FALSE FALSE FALSE FALSE FALSE
## 973 FALSE FALSE FALSE FALSE FALSE
## 974 FALSE FALSE FALSE FALSE FALSE
## 975 FALSE FALSE FALSE FALSE FALSE
## 976 FALSE FALSE FALSE FALSE FALSE
## 977 FALSE FALSE FALSE FALSE FALSE
## 978 FALSE FALSE FALSE FALSE FALSE
## 979 FALSE FALSE FALSE FALSE FALSE
## 980 FALSE FALSE FALSE FALSE FALSE
## 981 FALSE FALSE FALSE FALSE FALSE
## 982 FALSE FALSE FALSE FALSE FALSE
## 983 FALSE FALSE FALSE FALSE FALSE
## 984 FALSE FALSE FALSE FALSE FALSE
## 985 FALSE FALSE FALSE FALSE FALSE
## 986 FALSE FALSE FALSE FALSE FALSE
## 987 FALSE FALSE FALSE FALSE FALSE
## 988 FALSE FALSE FALSE FALSE FALSE
## 989 FALSE FALSE FALSE FALSE FALSE
## 990 FALSE FALSE FALSE FALSE FALSE
## 991 FALSE FALSE FALSE FALSE FALSE
## 992 FALSE FALSE FALSE FALSE FALSE
## 993 FALSE FALSE FALSE FALSE FALSE
## 994 FALSE FALSE FALSE FALSE FALSE
## 995 FALSE FALSE FALSE FALSE FALSE
## 996 FALSE FALSE FALSE FALSE FALSE
## 997 FALSE FALSE FALSE FALSE FALSE
## 998 FALSE FALSE FALSE FALSE FALSE
## 999 FALSE FALSE FALSE FALSE FALSE
## 1000 FALSE FALSE FALSE FALSE FALSE
## commute_distance_imp region_imp age_imp purchased_bike_imp
## 1 FALSE FALSE FALSE FALSE
## 2 FALSE FALSE FALSE FALSE
## 3 FALSE FALSE FALSE FALSE
## 4 FALSE FALSE FALSE FALSE
## 5 FALSE FALSE FALSE FALSE
## 6 FALSE FALSE FALSE FALSE
## 7 FALSE FALSE FALSE FALSE
## 8 FALSE FALSE FALSE FALSE
## 9 FALSE FALSE FALSE FALSE
## 10 FALSE FALSE TRUE FALSE
## 11 FALSE FALSE FALSE FALSE
## 12 FALSE FALSE FALSE FALSE
## 13 FALSE FALSE FALSE FALSE
## 14 FALSE FALSE FALSE FALSE
## 15 FALSE FALSE FALSE FALSE
## 16 FALSE FALSE FALSE FALSE
## 17 FALSE FALSE FALSE FALSE
## 18 FALSE FALSE FALSE FALSE
## 19 FALSE FALSE FALSE FALSE
## 20 FALSE FALSE FALSE FALSE
## 21 FALSE FALSE FALSE FALSE
## 22 FALSE FALSE FALSE FALSE
## 23 FALSE FALSE FALSE FALSE
## 24 FALSE FALSE FALSE FALSE
## 25 FALSE FALSE FALSE FALSE
## 26 FALSE FALSE FALSE FALSE
## 27 FALSE FALSE FALSE FALSE
## 28 FALSE FALSE FALSE FALSE
## 29 FALSE FALSE FALSE FALSE
## 30 FALSE FALSE FALSE FALSE
## 31 FALSE FALSE FALSE FALSE
## 32 FALSE FALSE FALSE FALSE
## 33 FALSE FALSE FALSE FALSE
## 34 FALSE FALSE FALSE FALSE
## 35 FALSE FALSE FALSE FALSE
## 36 FALSE FALSE FALSE FALSE
## 37 FALSE FALSE FALSE FALSE
## 38 FALSE FALSE FALSE FALSE
## 39 FALSE FALSE FALSE FALSE
## 40 FALSE FALSE FALSE FALSE
## 41 FALSE FALSE FALSE FALSE
## 42 FALSE FALSE FALSE FALSE
## 43 FALSE FALSE FALSE FALSE
## 44 FALSE FALSE FALSE FALSE
## 45 FALSE FALSE FALSE FALSE
## 46 FALSE FALSE FALSE FALSE
## 47 FALSE FALSE FALSE FALSE
## 48 FALSE FALSE FALSE FALSE
## 49 FALSE FALSE FALSE FALSE
## 50 FALSE FALSE FALSE FALSE
## 51 FALSE FALSE FALSE FALSE
## 52 FALSE FALSE FALSE FALSE
## 53 FALSE FALSE FALSE FALSE
## 54 FALSE FALSE FALSE FALSE
## 55 FALSE FALSE FALSE FALSE
## 56 FALSE FALSE FALSE FALSE
## 57 FALSE FALSE FALSE FALSE
## 58 FALSE FALSE FALSE FALSE
## 59 FALSE FALSE FALSE FALSE
## 60 FALSE FALSE FALSE FALSE
## 61 FALSE FALSE FALSE FALSE
## 62 FALSE FALSE FALSE FALSE
## 63 FALSE FALSE FALSE FALSE
## 64 FALSE FALSE FALSE FALSE
## 65 FALSE FALSE FALSE FALSE
## 66 FALSE FALSE FALSE FALSE
## 67 FALSE FALSE FALSE FALSE
## 68 FALSE FALSE FALSE FALSE
## 69 FALSE FALSE FALSE FALSE
## 70 FALSE FALSE FALSE FALSE
## 71 FALSE FALSE FALSE FALSE
## 72 FALSE FALSE FALSE FALSE
## 73 FALSE FALSE FALSE FALSE
## 74 FALSE FALSE FALSE FALSE
## 75 FALSE FALSE FALSE FALSE
## 76 FALSE FALSE FALSE FALSE
## 77 FALSE FALSE FALSE FALSE
## 78 FALSE FALSE FALSE FALSE
## 79 FALSE FALSE FALSE FALSE
## 80 FALSE FALSE FALSE FALSE
## 81 FALSE FALSE FALSE FALSE
## 82 FALSE FALSE FALSE FALSE
## 83 FALSE FALSE FALSE FALSE
## 84 FALSE FALSE FALSE FALSE
## 85 FALSE FALSE FALSE FALSE
## 86 FALSE FALSE FALSE FALSE
## 87 FALSE FALSE FALSE FALSE
## 88 FALSE FALSE FALSE FALSE
## 89 FALSE FALSE FALSE FALSE
## 90 FALSE FALSE FALSE FALSE
## 91 FALSE FALSE FALSE FALSE
## 92 FALSE FALSE FALSE FALSE
## 93 FALSE FALSE FALSE FALSE
## 94 FALSE FALSE FALSE FALSE
## 95 FALSE FALSE FALSE FALSE
## 96 FALSE FALSE FALSE FALSE
## 97 FALSE FALSE FALSE FALSE
## 98 FALSE FALSE FALSE FALSE
## 99 FALSE FALSE TRUE FALSE
## 100 FALSE FALSE FALSE FALSE
## 101 FALSE FALSE FALSE FALSE
## 102 FALSE FALSE FALSE FALSE
## 103 FALSE FALSE FALSE FALSE
## 104 FALSE FALSE FALSE FALSE
## 105 FALSE FALSE FALSE FALSE
## 106 FALSE FALSE FALSE FALSE
## 107 FALSE FALSE FALSE FALSE
## 108 FALSE FALSE FALSE FALSE
## 109 FALSE FALSE FALSE FALSE
## 110 FALSE FALSE FALSE FALSE
## 111 FALSE FALSE FALSE FALSE
## 112 FALSE FALSE FALSE FALSE
## 113 FALSE FALSE FALSE FALSE
## 114 FALSE FALSE FALSE FALSE
## 115 FALSE FALSE FALSE FALSE
## 116 FALSE FALSE FALSE FALSE
## 117 FALSE FALSE FALSE FALSE
## 118 FALSE FALSE FALSE FALSE
## 119 FALSE FALSE FALSE FALSE
## 120 FALSE FALSE FALSE FALSE
## 121 FALSE FALSE FALSE FALSE
## 122 FALSE FALSE FALSE FALSE
## 123 FALSE FALSE FALSE FALSE
## 124 FALSE FALSE FALSE FALSE
## 125 FALSE FALSE FALSE FALSE
## 126 FALSE FALSE FALSE FALSE
## 127 FALSE FALSE FALSE FALSE
## 128 FALSE FALSE FALSE FALSE
## 129 FALSE FALSE FALSE FALSE
## 130 FALSE FALSE FALSE FALSE
## 131 FALSE FALSE FALSE FALSE
## 132 FALSE FALSE FALSE FALSE
## 133 FALSE FALSE FALSE FALSE
## 134 FALSE FALSE FALSE FALSE
## 135 FALSE FALSE FALSE FALSE
## 136 FALSE FALSE FALSE FALSE
## 137 FALSE FALSE FALSE FALSE
## 138 FALSE FALSE FALSE FALSE
## 139 FALSE FALSE FALSE FALSE
## 140 FALSE FALSE FALSE FALSE
## 141 FALSE FALSE FALSE FALSE
## 142 FALSE FALSE FALSE FALSE
## 143 FALSE FALSE FALSE FALSE
## 144 FALSE FALSE FALSE FALSE
## 145 FALSE FALSE FALSE FALSE
## 146 FALSE FALSE FALSE FALSE
## 147 FALSE FALSE FALSE FALSE
## 148 FALSE FALSE FALSE FALSE
## 149 FALSE FALSE FALSE FALSE
## 150 FALSE FALSE FALSE FALSE
## 151 FALSE FALSE FALSE FALSE
## 152 FALSE FALSE FALSE FALSE
## 153 FALSE FALSE FALSE FALSE
## 154 FALSE FALSE FALSE FALSE
## 155 FALSE FALSE FALSE FALSE
## 156 FALSE FALSE FALSE FALSE
## 157 FALSE FALSE FALSE FALSE
## 158 FALSE FALSE FALSE FALSE
## 159 FALSE FALSE FALSE FALSE
## 160 FALSE FALSE FALSE FALSE
## 161 FALSE FALSE FALSE FALSE
## 162 FALSE FALSE FALSE FALSE
## 163 FALSE FALSE FALSE FALSE
## 164 FALSE FALSE FALSE FALSE
## 165 FALSE FALSE FALSE FALSE
## 166 FALSE FALSE FALSE FALSE
## 167 FALSE FALSE FALSE FALSE
## 168 FALSE FALSE FALSE FALSE
## 169 FALSE FALSE FALSE FALSE
## 170 FALSE FALSE FALSE FALSE
## 171 FALSE FALSE FALSE FALSE
## 172 FALSE FALSE FALSE FALSE
## 173 FALSE FALSE FALSE FALSE
## 174 FALSE FALSE FALSE FALSE
## 175 FALSE FALSE FALSE FALSE
## 176 FALSE FALSE FALSE FALSE
## 177 FALSE FALSE FALSE FALSE
## 178 FALSE FALSE FALSE FALSE
## 179 FALSE FALSE FALSE FALSE
## 180 FALSE FALSE FALSE FALSE
## 181 FALSE FALSE FALSE FALSE
## 182 FALSE FALSE FALSE FALSE
## 183 FALSE FALSE FALSE FALSE
## 184 FALSE FALSE FALSE FALSE
## 185 FALSE FALSE FALSE FALSE
## 186 FALSE FALSE FALSE FALSE
## 187 FALSE FALSE FALSE FALSE
## 188 FALSE FALSE FALSE FALSE
## 189 FALSE FALSE FALSE FALSE
## 190 FALSE FALSE FALSE FALSE
## 191 FALSE FALSE FALSE FALSE
## 192 FALSE FALSE FALSE FALSE
## 193 FALSE FALSE FALSE FALSE
## 194 FALSE FALSE FALSE FALSE
## 195 FALSE FALSE FALSE FALSE
## 196 FALSE FALSE FALSE FALSE
## 197 FALSE FALSE FALSE FALSE
## 198 FALSE FALSE FALSE FALSE
## 199 FALSE FALSE FALSE FALSE
## 200 FALSE FALSE FALSE FALSE
## 201 FALSE FALSE FALSE FALSE
## 202 FALSE FALSE FALSE FALSE
## 203 FALSE FALSE FALSE FALSE
## 204 FALSE FALSE FALSE FALSE
## 205 FALSE FALSE FALSE FALSE
## 206 FALSE FALSE FALSE FALSE
## 207 FALSE FALSE FALSE FALSE
## 208 FALSE FALSE FALSE FALSE
## 209 FALSE FALSE FALSE FALSE
## 210 FALSE FALSE FALSE FALSE
## 211 FALSE FALSE FALSE FALSE
## 212 FALSE FALSE FALSE FALSE
## 213 FALSE FALSE FALSE FALSE
## 214 FALSE FALSE FALSE FALSE
## 215 FALSE FALSE FALSE FALSE
## 216 FALSE FALSE FALSE FALSE
## 217 FALSE FALSE FALSE FALSE
## 218 FALSE FALSE FALSE FALSE
## 219 FALSE FALSE FALSE FALSE
## 220 FALSE FALSE FALSE FALSE
## 221 FALSE FALSE FALSE FALSE
## 222 FALSE FALSE FALSE FALSE
## 223 FALSE FALSE FALSE FALSE
## 224 FALSE FALSE FALSE FALSE
## 225 FALSE FALSE FALSE FALSE
## 226 FALSE FALSE TRUE FALSE
## 227 FALSE FALSE FALSE FALSE
## 228 FALSE FALSE FALSE FALSE
## 229 FALSE FALSE FALSE FALSE
## 230 FALSE FALSE FALSE FALSE
## 231 FALSE FALSE FALSE FALSE
## 232 FALSE FALSE FALSE FALSE
## 233 FALSE FALSE FALSE FALSE
## 234 FALSE FALSE FALSE FALSE
## 235 FALSE FALSE FALSE FALSE
## 236 FALSE FALSE FALSE FALSE
## 237 FALSE FALSE FALSE FALSE
## 238 FALSE FALSE FALSE FALSE
## 239 FALSE FALSE FALSE FALSE
## 240 FALSE FALSE FALSE FALSE
## 241 FALSE FALSE FALSE FALSE
## 242 FALSE FALSE FALSE FALSE
## 243 FALSE FALSE FALSE FALSE
## 244 FALSE FALSE FALSE FALSE
## 245 FALSE FALSE FALSE FALSE
## 246 FALSE FALSE FALSE FALSE
## 247 FALSE FALSE FALSE FALSE
## 248 FALSE FALSE FALSE FALSE
## 249 FALSE FALSE FALSE FALSE
## 250 FALSE FALSE FALSE FALSE
## 251 FALSE FALSE FALSE FALSE
## 252 FALSE FALSE FALSE FALSE
## 253 FALSE FALSE FALSE FALSE
## 254 FALSE FALSE FALSE FALSE
## 255 FALSE FALSE FALSE FALSE
## 256 FALSE FALSE FALSE FALSE
## 257 FALSE FALSE FALSE FALSE
## 258 FALSE FALSE FALSE FALSE
## 259 FALSE FALSE FALSE FALSE
## 260 FALSE FALSE FALSE FALSE
## 261 FALSE FALSE FALSE FALSE
## 262 FALSE FALSE FALSE FALSE
## 263 FALSE FALSE FALSE FALSE
## 264 FALSE FALSE FALSE FALSE
## 265 FALSE FALSE FALSE FALSE
## 266 FALSE FALSE FALSE FALSE
## 267 FALSE FALSE FALSE FALSE
## 268 FALSE FALSE FALSE FALSE
## 269 FALSE FALSE FALSE FALSE
## 270 FALSE FALSE FALSE FALSE
## 271 FALSE FALSE FALSE FALSE
## 272 FALSE FALSE FALSE FALSE
## 273 FALSE FALSE FALSE FALSE
## 274 FALSE FALSE FALSE FALSE
## 275 FALSE FALSE FALSE FALSE
## 276 FALSE FALSE FALSE FALSE
## 277 FALSE FALSE FALSE FALSE
## 278 FALSE FALSE FALSE FALSE
## 279 FALSE FALSE FALSE FALSE
## 280 FALSE FALSE FALSE FALSE
## 281 FALSE FALSE FALSE FALSE
## 282 FALSE FALSE FALSE FALSE
## 283 FALSE FALSE FALSE FALSE
## 284 FALSE FALSE FALSE FALSE
## 285 FALSE FALSE FALSE FALSE
## 286 FALSE FALSE FALSE FALSE
## 287 FALSE FALSE FALSE FALSE
## 288 FALSE FALSE FALSE FALSE
## 289 FALSE FALSE FALSE FALSE
## 290 FALSE FALSE FALSE FALSE
## 291 FALSE FALSE FALSE FALSE
## 292 FALSE FALSE FALSE FALSE
## 293 FALSE FALSE FALSE FALSE
## 294 FALSE FALSE FALSE FALSE
## 295 FALSE FALSE FALSE FALSE
## 296 FALSE FALSE FALSE FALSE
## 297 FALSE FALSE FALSE FALSE
## 298 FALSE FALSE FALSE FALSE
## 299 FALSE FALSE FALSE FALSE
## 300 FALSE FALSE FALSE FALSE
## 301 FALSE FALSE FALSE FALSE
## 302 FALSE FALSE FALSE FALSE
## 303 FALSE FALSE FALSE FALSE
## 304 FALSE FALSE FALSE FALSE
## 305 FALSE FALSE FALSE FALSE
## 306 FALSE FALSE FALSE FALSE
## 307 FALSE FALSE FALSE FALSE
## 308 FALSE FALSE FALSE FALSE
## 309 FALSE FALSE FALSE FALSE
## 310 FALSE FALSE FALSE FALSE
## 311 FALSE FALSE FALSE FALSE
## 312 FALSE FALSE FALSE FALSE
## 313 FALSE FALSE FALSE FALSE
## 314 FALSE FALSE FALSE FALSE
## 315 FALSE FALSE FALSE FALSE
## 316 FALSE FALSE FALSE FALSE
## 317 FALSE FALSE FALSE FALSE
## 318 FALSE FALSE FALSE FALSE
## 319 FALSE FALSE FALSE FALSE
## 320 FALSE FALSE FALSE FALSE
## 321 FALSE FALSE FALSE FALSE
## 322 FALSE FALSE FALSE FALSE
## 323 FALSE FALSE FALSE FALSE
## 324 FALSE FALSE FALSE FALSE
## 325 FALSE FALSE FALSE FALSE
## 326 FALSE FALSE FALSE FALSE
## 327 FALSE FALSE FALSE FALSE
## 328 FALSE FALSE FALSE FALSE
## 329 FALSE FALSE FALSE FALSE
## 330 FALSE FALSE FALSE FALSE
## 331 FALSE FALSE FALSE FALSE
## 332 FALSE FALSE FALSE FALSE
## 333 FALSE FALSE FALSE FALSE
## 334 FALSE FALSE FALSE FALSE
## 335 FALSE FALSE FALSE FALSE
## 336 FALSE FALSE FALSE FALSE
## 337 FALSE FALSE FALSE FALSE
## 338 FALSE FALSE FALSE FALSE
## 339 FALSE FALSE FALSE FALSE
## 340 FALSE FALSE FALSE FALSE
## 341 FALSE FALSE FALSE FALSE
## 342 FALSE FALSE FALSE FALSE
## 343 FALSE FALSE FALSE FALSE
## 344 FALSE FALSE FALSE FALSE
## 345 FALSE FALSE FALSE FALSE
## 346 FALSE FALSE FALSE FALSE
## 347 FALSE FALSE FALSE FALSE
## 348 FALSE FALSE FALSE FALSE
## 349 FALSE FALSE FALSE FALSE
## 350 FALSE FALSE FALSE FALSE
## 351 FALSE FALSE FALSE FALSE
## 352 FALSE FALSE FALSE FALSE
## 353 FALSE FALSE FALSE FALSE
## 354 FALSE FALSE FALSE FALSE
## 355 FALSE FALSE FALSE FALSE
## 356 FALSE FALSE FALSE FALSE
## 357 FALSE FALSE FALSE FALSE
## 358 FALSE FALSE FALSE FALSE
## 359 FALSE FALSE FALSE FALSE
## 360 FALSE FALSE FALSE FALSE
## 361 FALSE FALSE FALSE FALSE
## 362 FALSE FALSE FALSE FALSE
## 363 FALSE FALSE FALSE FALSE
## 364 FALSE FALSE FALSE FALSE
## 365 FALSE FALSE FALSE FALSE
## 366 FALSE FALSE FALSE FALSE
## 367 FALSE FALSE FALSE FALSE
## 368 FALSE FALSE FALSE FALSE
## 369 FALSE FALSE FALSE FALSE
## 370 FALSE FALSE FALSE FALSE
## 371 FALSE FALSE FALSE FALSE
## 372 FALSE FALSE TRUE FALSE
## 373 FALSE FALSE FALSE FALSE
## 374 FALSE FALSE FALSE FALSE
## 375 FALSE FALSE FALSE FALSE
## 376 FALSE FALSE FALSE FALSE
## 377 FALSE FALSE FALSE FALSE
## 378 FALSE FALSE FALSE FALSE
## 379 FALSE FALSE FALSE FALSE
## 380 FALSE FALSE FALSE FALSE
## 381 FALSE FALSE FALSE FALSE
## 382 FALSE FALSE FALSE FALSE
## 383 FALSE FALSE FALSE FALSE
## 384 FALSE FALSE FALSE FALSE
## 385 FALSE FALSE FALSE FALSE
## 386 FALSE FALSE FALSE FALSE
## 387 FALSE FALSE FALSE FALSE
## 388 FALSE FALSE FALSE FALSE
## 389 FALSE FALSE FALSE FALSE
## 390 FALSE FALSE FALSE FALSE
## 391 FALSE FALSE FALSE FALSE
## 392 FALSE FALSE FALSE FALSE
## 393 FALSE FALSE FALSE FALSE
## 394 FALSE FALSE FALSE FALSE
## 395 FALSE FALSE FALSE FALSE
## 396 FALSE FALSE FALSE FALSE
## 397 FALSE FALSE FALSE FALSE
## 398 FALSE FALSE FALSE FALSE
## 399 FALSE FALSE FALSE FALSE
## 400 FALSE FALSE FALSE FALSE
## 401 FALSE FALSE FALSE FALSE
## 402 FALSE FALSE FALSE FALSE
## 403 FALSE FALSE FALSE FALSE
## 404 FALSE FALSE FALSE FALSE
## 405 FALSE FALSE FALSE FALSE
## 406 FALSE FALSE FALSE FALSE
## 407 FALSE FALSE FALSE FALSE
## 408 FALSE FALSE FALSE FALSE
## 409 FALSE FALSE FALSE FALSE
## 410 FALSE FALSE FALSE FALSE
## 411 FALSE FALSE FALSE FALSE
## 412 FALSE FALSE FALSE FALSE
## 413 FALSE FALSE FALSE FALSE
## 414 FALSE FALSE FALSE FALSE
## 415 FALSE FALSE FALSE FALSE
## 416 FALSE FALSE FALSE FALSE
## 417 FALSE FALSE FALSE FALSE
## 418 FALSE FALSE FALSE FALSE
## 419 FALSE FALSE FALSE FALSE
## 420 FALSE FALSE FALSE FALSE
## 421 FALSE FALSE FALSE FALSE
## 422 FALSE FALSE FALSE FALSE
## 423 FALSE FALSE FALSE FALSE
## 424 FALSE FALSE FALSE FALSE
## 425 FALSE FALSE FALSE FALSE
## 426 FALSE FALSE FALSE FALSE
## 427 FALSE FALSE FALSE FALSE
## 428 FALSE FALSE FALSE FALSE
## 429 FALSE FALSE FALSE FALSE
## 430 FALSE FALSE FALSE FALSE
## 431 FALSE FALSE FALSE FALSE
## 432 FALSE FALSE FALSE FALSE
## 433 FALSE FALSE FALSE FALSE
## 434 FALSE FALSE FALSE FALSE
## 435 FALSE FALSE FALSE FALSE
## 436 FALSE FALSE FALSE FALSE
## 437 FALSE FALSE FALSE FALSE
## 438 FALSE FALSE FALSE FALSE
## 439 FALSE FALSE FALSE FALSE
## 440 FALSE FALSE FALSE FALSE
## 441 FALSE FALSE FALSE FALSE
## 442 FALSE FALSE FALSE FALSE
## 443 FALSE FALSE FALSE FALSE
## 444 FALSE FALSE FALSE FALSE
## 445 FALSE FALSE FALSE FALSE
## 446 FALSE FALSE FALSE FALSE
## 447 FALSE FALSE FALSE FALSE
## 448 FALSE FALSE FALSE FALSE
## 449 FALSE FALSE FALSE FALSE
## 450 FALSE FALSE FALSE FALSE
## 451 FALSE FALSE FALSE FALSE
## 452 FALSE FALSE FALSE FALSE
## 453 FALSE FALSE FALSE FALSE
## 454 FALSE FALSE FALSE FALSE
## 455 FALSE FALSE FALSE FALSE
## 456 FALSE FALSE FALSE FALSE
## 457 FALSE FALSE FALSE FALSE
## 458 FALSE FALSE FALSE FALSE
## 459 FALSE FALSE FALSE FALSE
## 460 FALSE FALSE FALSE FALSE
## 461 FALSE FALSE FALSE FALSE
## 462 FALSE FALSE FALSE FALSE
## 463 FALSE FALSE FALSE FALSE
## 464 FALSE FALSE FALSE FALSE
## 465 FALSE FALSE FALSE FALSE
## 466 FALSE FALSE FALSE FALSE
## 467 FALSE FALSE FALSE FALSE
## 468 FALSE FALSE FALSE FALSE
## 469 FALSE FALSE FALSE FALSE
## 470 FALSE FALSE FALSE FALSE
## 471 FALSE FALSE FALSE FALSE
## 472 FALSE FALSE FALSE FALSE
## 473 FALSE FALSE FALSE FALSE
## 474 FALSE FALSE FALSE FALSE
## 475 FALSE FALSE FALSE FALSE
## 476 FALSE FALSE FALSE FALSE
## 477 FALSE FALSE FALSE FALSE
## 478 FALSE FALSE FALSE FALSE
## 479 FALSE FALSE FALSE FALSE
## 480 FALSE FALSE FALSE FALSE
## 481 FALSE FALSE FALSE FALSE
## 482 FALSE FALSE FALSE FALSE
## 483 FALSE FALSE FALSE FALSE
## 484 FALSE FALSE FALSE FALSE
## 485 FALSE FALSE FALSE FALSE
## 486 FALSE FALSE FALSE FALSE
## 487 FALSE FALSE FALSE FALSE
## 488 FALSE FALSE FALSE FALSE
## 489 FALSE FALSE FALSE FALSE
## 490 FALSE FALSE FALSE FALSE
## 491 FALSE FALSE FALSE FALSE
## 492 FALSE FALSE FALSE FALSE
## 493 FALSE FALSE FALSE FALSE
## 494 FALSE FALSE FALSE FALSE
## 495 FALSE FALSE FALSE FALSE
## 496 FALSE FALSE FALSE FALSE
## 497 FALSE FALSE FALSE FALSE
## 498 FALSE FALSE FALSE FALSE
## 499 FALSE FALSE FALSE FALSE
## 500 FALSE FALSE FALSE FALSE
## 501 FALSE FALSE FALSE FALSE
## 502 FALSE FALSE FALSE FALSE
## 503 FALSE FALSE FALSE FALSE
## 504 FALSE FALSE FALSE FALSE
## 505 FALSE FALSE FALSE FALSE
## 506 FALSE FALSE FALSE FALSE
## 507 FALSE FALSE FALSE FALSE
## 508 FALSE FALSE FALSE FALSE
## 509 FALSE FALSE FALSE FALSE
## 510 FALSE FALSE FALSE FALSE
## 511 FALSE FALSE FALSE FALSE
## 512 FALSE FALSE FALSE FALSE
## 513 FALSE FALSE FALSE FALSE
## 514 FALSE FALSE FALSE FALSE
## 515 FALSE FALSE FALSE FALSE
## 516 FALSE FALSE FALSE FALSE
## 517 FALSE FALSE FALSE FALSE
## 518 FALSE FALSE FALSE FALSE
## 519 FALSE FALSE FALSE FALSE
## 520 FALSE FALSE FALSE FALSE
## 521 FALSE FALSE FALSE FALSE
## 522 FALSE FALSE FALSE FALSE
## 523 FALSE FALSE FALSE FALSE
## 524 FALSE FALSE FALSE FALSE
## 525 FALSE FALSE FALSE FALSE
## 526 FALSE FALSE FALSE FALSE
## 527 FALSE FALSE FALSE FALSE
## 528 FALSE FALSE FALSE FALSE
## 529 FALSE FALSE FALSE FALSE
## 530 FALSE FALSE FALSE FALSE
## 531 FALSE FALSE FALSE FALSE
## 532 FALSE FALSE FALSE FALSE
## 533 FALSE FALSE FALSE FALSE
## 534 FALSE FALSE FALSE FALSE
## 535 FALSE FALSE FALSE FALSE
## 536 FALSE FALSE FALSE FALSE
## 537 FALSE FALSE FALSE FALSE
## 538 FALSE FALSE FALSE FALSE
## 539 FALSE FALSE FALSE FALSE
## 540 FALSE FALSE FALSE FALSE
## 541 FALSE FALSE FALSE FALSE
## 542 FALSE FALSE FALSE FALSE
## 543 FALSE FALSE FALSE FALSE
## 544 FALSE FALSE FALSE FALSE
## 545 FALSE FALSE FALSE FALSE
## 546 FALSE FALSE FALSE FALSE
## 547 FALSE FALSE FALSE FALSE
## 548 FALSE FALSE FALSE FALSE
## 549 FALSE FALSE FALSE FALSE
## 550 FALSE FALSE FALSE FALSE
## 551 FALSE FALSE FALSE FALSE
## 552 FALSE FALSE FALSE FALSE
## 553 FALSE FALSE FALSE FALSE
## 554 FALSE FALSE FALSE FALSE
## 555 FALSE FALSE TRUE FALSE
## 556 FALSE FALSE FALSE FALSE
## 557 FALSE FALSE FALSE FALSE
## 558 FALSE FALSE FALSE FALSE
## 559 FALSE FALSE FALSE FALSE
## 560 FALSE FALSE FALSE FALSE
## 561 FALSE FALSE FALSE FALSE
## 562 FALSE FALSE FALSE FALSE
## 563 FALSE FALSE FALSE FALSE
## 564 FALSE FALSE FALSE FALSE
## 565 FALSE FALSE FALSE FALSE
## 566 FALSE FALSE FALSE FALSE
## 567 FALSE FALSE FALSE FALSE
## 568 FALSE FALSE FALSE FALSE
## 569 FALSE FALSE FALSE FALSE
## 570 FALSE FALSE FALSE FALSE
## 571 FALSE FALSE FALSE FALSE
## 572 FALSE FALSE FALSE FALSE
## 573 FALSE FALSE FALSE FALSE
## 574 FALSE FALSE FALSE FALSE
## 575 FALSE FALSE FALSE FALSE
## 576 FALSE FALSE FALSE FALSE
## 577 FALSE FALSE FALSE FALSE
## 578 FALSE FALSE FALSE FALSE
## 579 FALSE FALSE FALSE FALSE
## 580 FALSE FALSE FALSE FALSE
## 581 FALSE FALSE FALSE FALSE
## 582 FALSE FALSE FALSE FALSE
## 583 FALSE FALSE FALSE FALSE
## 584 FALSE FALSE FALSE FALSE
## 585 FALSE FALSE FALSE FALSE
## 586 FALSE FALSE FALSE FALSE
## 587 FALSE FALSE FALSE FALSE
## 588 FALSE FALSE FALSE FALSE
## 589 FALSE FALSE FALSE FALSE
## 590 FALSE FALSE FALSE FALSE
## 591 FALSE FALSE FALSE FALSE
## 592 FALSE FALSE FALSE FALSE
## 593 FALSE FALSE FALSE FALSE
## 594 FALSE FALSE FALSE FALSE
## 595 FALSE FALSE FALSE FALSE
## 596 FALSE FALSE FALSE FALSE
## 597 FALSE FALSE FALSE FALSE
## 598 FALSE FALSE FALSE FALSE
## 599 FALSE FALSE FALSE FALSE
## 600 FALSE FALSE FALSE FALSE
## 601 FALSE FALSE FALSE FALSE
## 602 FALSE FALSE FALSE FALSE
## 603 FALSE FALSE FALSE FALSE
## 604 FALSE FALSE FALSE FALSE
## 605 FALSE FALSE FALSE FALSE
## 606 FALSE FALSE FALSE FALSE
## 607 FALSE FALSE FALSE FALSE
## 608 FALSE FALSE FALSE FALSE
## 609 FALSE FALSE FALSE FALSE
## 610 FALSE FALSE FALSE FALSE
## 611 FALSE FALSE FALSE FALSE
## 612 FALSE FALSE FALSE FALSE
## 613 FALSE FALSE FALSE FALSE
## 614 FALSE FALSE FALSE FALSE
## 615 FALSE FALSE FALSE FALSE
## 616 FALSE FALSE FALSE FALSE
## 617 FALSE FALSE FALSE FALSE
## 618 FALSE FALSE FALSE FALSE
## 619 FALSE FALSE FALSE FALSE
## 620 FALSE FALSE FALSE FALSE
## 621 FALSE FALSE FALSE FALSE
## 622 FALSE FALSE FALSE FALSE
## 623 FALSE FALSE FALSE FALSE
## 624 FALSE FALSE FALSE FALSE
## 625 FALSE FALSE FALSE FALSE
## 626 FALSE FALSE FALSE FALSE
## 627 FALSE FALSE FALSE FALSE
## 628 FALSE FALSE FALSE FALSE
## 629 FALSE FALSE FALSE FALSE
## 630 FALSE FALSE FALSE FALSE
## 631 FALSE FALSE FALSE FALSE
## 632 FALSE FALSE FALSE FALSE
## 633 FALSE FALSE FALSE FALSE
## 634 FALSE FALSE FALSE FALSE
## 635 FALSE FALSE FALSE FALSE
## 636 FALSE FALSE FALSE FALSE
## 637 FALSE FALSE FALSE FALSE
## 638 FALSE FALSE FALSE FALSE
## 639 FALSE FALSE FALSE FALSE
## 640 FALSE FALSE FALSE FALSE
## 641 FALSE FALSE FALSE FALSE
## 642 FALSE FALSE FALSE FALSE
## 643 FALSE FALSE FALSE FALSE
## 644 FALSE FALSE FALSE FALSE
## 645 FALSE FALSE FALSE FALSE
## 646 FALSE FALSE FALSE FALSE
## 647 FALSE FALSE FALSE FALSE
## 648 FALSE FALSE FALSE FALSE
## 649 FALSE FALSE FALSE FALSE
## 650 FALSE FALSE FALSE FALSE
## 651 FALSE FALSE FALSE FALSE
## 652 FALSE FALSE FALSE FALSE
## 653 FALSE FALSE FALSE FALSE
## 654 FALSE FALSE FALSE FALSE
## 655 FALSE FALSE FALSE FALSE
## 656 FALSE FALSE FALSE FALSE
## 657 FALSE FALSE FALSE FALSE
## 658 FALSE FALSE FALSE FALSE
## 659 FALSE FALSE FALSE FALSE
## 660 FALSE FALSE FALSE FALSE
## 661 FALSE FALSE FALSE FALSE
## 662 FALSE FALSE FALSE FALSE
## 663 FALSE FALSE FALSE FALSE
## 664 FALSE FALSE FALSE FALSE
## 665 FALSE FALSE FALSE FALSE
## 666 FALSE FALSE FALSE FALSE
## 667 FALSE FALSE FALSE FALSE
## 668 FALSE FALSE FALSE FALSE
## 669 FALSE FALSE FALSE FALSE
## 670 FALSE FALSE FALSE FALSE
## 671 FALSE FALSE FALSE FALSE
## 672 FALSE FALSE FALSE FALSE
## 673 FALSE FALSE FALSE FALSE
## 674 FALSE FALSE FALSE FALSE
## 675 FALSE FALSE FALSE FALSE
## 676 FALSE FALSE FALSE FALSE
## 677 FALSE FALSE FALSE FALSE
## 678 FALSE FALSE FALSE FALSE
## 679 FALSE FALSE FALSE FALSE
## 680 FALSE FALSE FALSE FALSE
## 681 FALSE FALSE FALSE FALSE
## 682 FALSE FALSE FALSE FALSE
## 683 FALSE FALSE FALSE FALSE
## 684 FALSE FALSE FALSE FALSE
## 685 FALSE FALSE FALSE FALSE
## 686 FALSE FALSE FALSE FALSE
## 687 FALSE FALSE FALSE FALSE
## 688 FALSE FALSE FALSE FALSE
## 689 FALSE FALSE TRUE FALSE
## 690 FALSE FALSE FALSE FALSE
## 691 FALSE FALSE FALSE FALSE
## 692 FALSE FALSE FALSE FALSE
## 693 FALSE FALSE FALSE FALSE
## 694 FALSE FALSE FALSE FALSE
## 695 FALSE FALSE FALSE FALSE
## 696 FALSE FALSE FALSE FALSE
## 697 FALSE FALSE FALSE FALSE
## 698 FALSE FALSE FALSE FALSE
## 699 FALSE FALSE FALSE FALSE
## 700 FALSE FALSE FALSE FALSE
## 701 FALSE FALSE FALSE FALSE
## 702 FALSE FALSE FALSE FALSE
## 703 FALSE FALSE FALSE FALSE
## 704 FALSE FALSE FALSE FALSE
## 705 FALSE FALSE FALSE FALSE
## 706 FALSE FALSE FALSE FALSE
## 707 FALSE FALSE FALSE FALSE
## 708 FALSE FALSE FALSE FALSE
## 709 FALSE FALSE FALSE FALSE
## 710 FALSE FALSE FALSE FALSE
## 711 FALSE FALSE FALSE FALSE
## 712 FALSE FALSE FALSE FALSE
## 713 FALSE FALSE FALSE FALSE
## 714 FALSE FALSE FALSE FALSE
## 715 FALSE FALSE FALSE FALSE
## 716 FALSE FALSE FALSE FALSE
## 717 FALSE FALSE FALSE FALSE
## 718 FALSE FALSE FALSE FALSE
## 719 FALSE FALSE FALSE FALSE
## 720 FALSE FALSE FALSE FALSE
## 721 FALSE FALSE FALSE FALSE
## 722 FALSE FALSE FALSE FALSE
## 723 FALSE FALSE FALSE FALSE
## 724 FALSE FALSE FALSE FALSE
## 725 FALSE FALSE FALSE FALSE
## 726 FALSE FALSE FALSE FALSE
## 727 FALSE FALSE FALSE FALSE
## 728 FALSE FALSE FALSE FALSE
## 729 FALSE FALSE FALSE FALSE
## 730 FALSE FALSE FALSE FALSE
## 731 FALSE FALSE FALSE FALSE
## 732 FALSE FALSE FALSE FALSE
## 733 FALSE FALSE FALSE FALSE
## 734 FALSE FALSE FALSE FALSE
## 735 FALSE FALSE FALSE FALSE
## 736 FALSE FALSE FALSE FALSE
## 737 FALSE FALSE FALSE FALSE
## 738 FALSE FALSE FALSE FALSE
## 739 FALSE FALSE FALSE FALSE
## 740 FALSE FALSE FALSE FALSE
## 741 FALSE FALSE FALSE FALSE
## 742 FALSE FALSE FALSE FALSE
## 743 FALSE FALSE FALSE FALSE
## 744 FALSE FALSE FALSE FALSE
## 745 FALSE FALSE FALSE FALSE
## 746 FALSE FALSE FALSE FALSE
## 747 FALSE FALSE FALSE FALSE
## 748 FALSE FALSE FALSE FALSE
## 749 FALSE FALSE FALSE FALSE
## 750 FALSE FALSE FALSE FALSE
## 751 FALSE FALSE FALSE FALSE
## 752 FALSE FALSE FALSE FALSE
## 753 FALSE FALSE FALSE FALSE
## 754 FALSE FALSE FALSE FALSE
## 755 FALSE FALSE FALSE FALSE
## 756 FALSE FALSE FALSE FALSE
## 757 FALSE FALSE FALSE FALSE
## 758 FALSE FALSE FALSE FALSE
## 759 FALSE FALSE FALSE FALSE
## 760 FALSE FALSE FALSE FALSE
## 761 FALSE FALSE FALSE FALSE
## 762 FALSE FALSE FALSE FALSE
## 763 FALSE FALSE FALSE FALSE
## 764 FALSE FALSE FALSE FALSE
## 765 FALSE FALSE FALSE FALSE
## 766 FALSE FALSE FALSE FALSE
## 767 FALSE FALSE FALSE FALSE
## 768 FALSE FALSE FALSE FALSE
## 769 FALSE FALSE FALSE FALSE
## 770 FALSE FALSE FALSE FALSE
## 771 FALSE FALSE TRUE FALSE
## 772 FALSE FALSE FALSE FALSE
## 773 FALSE FALSE FALSE FALSE
## 774 FALSE FALSE FALSE FALSE
## 775 FALSE FALSE FALSE FALSE
## 776 FALSE FALSE FALSE FALSE
## 777 FALSE FALSE FALSE FALSE
## 778 FALSE FALSE FALSE FALSE
## 779 FALSE FALSE FALSE FALSE
## 780 FALSE FALSE FALSE FALSE
## 781 FALSE FALSE FALSE FALSE
## 782 FALSE FALSE FALSE FALSE
## 783 FALSE FALSE FALSE FALSE
## 784 FALSE FALSE FALSE FALSE
## 785 FALSE FALSE FALSE FALSE
## 786 FALSE FALSE FALSE FALSE
## 787 FALSE FALSE FALSE FALSE
## 788 FALSE FALSE FALSE FALSE
## 789 FALSE FALSE FALSE FALSE
## 790 FALSE FALSE FALSE FALSE
## 791 FALSE FALSE FALSE FALSE
## 792 FALSE FALSE FALSE FALSE
## 793 FALSE FALSE FALSE FALSE
## 794 FALSE FALSE FALSE FALSE
## 795 FALSE FALSE FALSE FALSE
## 796 FALSE FALSE FALSE FALSE
## 797 FALSE FALSE FALSE FALSE
## 798 FALSE FALSE FALSE FALSE
## 799 FALSE FALSE FALSE FALSE
## 800 FALSE FALSE FALSE FALSE
## 801 FALSE FALSE FALSE FALSE
## 802 FALSE FALSE FALSE FALSE
## 803 FALSE FALSE FALSE FALSE
## 804 FALSE FALSE FALSE FALSE
## 805 FALSE FALSE FALSE FALSE
## 806 FALSE FALSE FALSE FALSE
## 807 FALSE FALSE FALSE FALSE
## 808 FALSE FALSE FALSE FALSE
## 809 FALSE FALSE FALSE FALSE
## 810 FALSE FALSE FALSE FALSE
## 811 FALSE FALSE FALSE FALSE
## 812 FALSE FALSE FALSE FALSE
## 813 FALSE FALSE FALSE FALSE
## 814 FALSE FALSE FALSE FALSE
## 815 FALSE FALSE FALSE FALSE
## 816 FALSE FALSE FALSE FALSE
## 817 FALSE FALSE FALSE FALSE
## 818 FALSE FALSE FALSE FALSE
## 819 FALSE FALSE FALSE FALSE
## 820 FALSE FALSE FALSE FALSE
## 821 FALSE FALSE FALSE FALSE
## 822 FALSE FALSE FALSE FALSE
## 823 FALSE FALSE FALSE FALSE
## 824 FALSE FALSE FALSE FALSE
## 825 FALSE FALSE FALSE FALSE
## 826 FALSE FALSE FALSE FALSE
## 827 FALSE FALSE FALSE FALSE
## 828 FALSE FALSE FALSE FALSE
## 829 FALSE FALSE FALSE FALSE
## 830 FALSE FALSE FALSE FALSE
## 831 FALSE FALSE FALSE FALSE
## 832 FALSE FALSE FALSE FALSE
## 833 FALSE FALSE FALSE FALSE
## 834 FALSE FALSE FALSE FALSE
## 835 FALSE FALSE FALSE FALSE
## 836 FALSE FALSE FALSE FALSE
## 837 FALSE FALSE FALSE FALSE
## 838 FALSE FALSE FALSE FALSE
## 839 FALSE FALSE FALSE FALSE
## 840 FALSE FALSE FALSE FALSE
## 841 FALSE FALSE FALSE FALSE
## 842 FALSE FALSE FALSE FALSE
## 843 FALSE FALSE FALSE FALSE
## 844 FALSE FALSE FALSE FALSE
## 845 FALSE FALSE FALSE FALSE
## 846 FALSE FALSE FALSE FALSE
## 847 FALSE FALSE FALSE FALSE
## 848 FALSE FALSE FALSE FALSE
## 849 FALSE FALSE FALSE FALSE
## 850 FALSE FALSE FALSE FALSE
## 851 FALSE FALSE FALSE FALSE
## 852 FALSE FALSE FALSE FALSE
## 853 FALSE FALSE FALSE FALSE
## 854 FALSE FALSE FALSE FALSE
## 855 FALSE FALSE FALSE FALSE
## 856 FALSE FALSE FALSE FALSE
## 857 FALSE FALSE FALSE FALSE
## 858 FALSE FALSE FALSE FALSE
## 859 FALSE FALSE FALSE FALSE
## 860 FALSE FALSE FALSE FALSE
## 861 FALSE FALSE FALSE FALSE
## 862 FALSE FALSE FALSE FALSE
## 863 FALSE FALSE FALSE FALSE
## 864 FALSE FALSE FALSE FALSE
## 865 FALSE FALSE FALSE FALSE
## 866 FALSE FALSE FALSE FALSE
## 867 FALSE FALSE FALSE FALSE
## 868 FALSE FALSE FALSE FALSE
## 869 FALSE FALSE FALSE FALSE
## 870 FALSE FALSE FALSE FALSE
## 871 FALSE FALSE FALSE FALSE
## 872 FALSE FALSE FALSE FALSE
## 873 FALSE FALSE FALSE FALSE
## 874 FALSE FALSE FALSE FALSE
## 875 FALSE FALSE FALSE FALSE
## 876 FALSE FALSE FALSE FALSE
## 877 FALSE FALSE FALSE FALSE
## 878 FALSE FALSE FALSE FALSE
## 879 FALSE FALSE FALSE FALSE
## 880 FALSE FALSE FALSE FALSE
## 881 FALSE FALSE FALSE FALSE
## 882 FALSE FALSE FALSE FALSE
## 883 FALSE FALSE FALSE FALSE
## 884 FALSE FALSE FALSE FALSE
## 885 FALSE FALSE FALSE FALSE
## 886 FALSE FALSE FALSE FALSE
## 887 FALSE FALSE FALSE FALSE
## 888 FALSE FALSE FALSE FALSE
## 889 FALSE FALSE FALSE FALSE
## 890 FALSE FALSE FALSE FALSE
## 891 FALSE FALSE FALSE FALSE
## 892 FALSE FALSE FALSE FALSE
## 893 FALSE FALSE FALSE FALSE
## 894 FALSE FALSE FALSE FALSE
## 895 FALSE FALSE FALSE FALSE
## 896 FALSE FALSE FALSE FALSE
## 897 FALSE FALSE FALSE FALSE
## 898 FALSE FALSE FALSE FALSE
## 899 FALSE FALSE FALSE FALSE
## 900 FALSE FALSE FALSE FALSE
## 901 FALSE FALSE FALSE FALSE
## 902 FALSE FALSE FALSE FALSE
## 903 FALSE FALSE FALSE FALSE
## 904 FALSE FALSE FALSE FALSE
## 905 FALSE FALSE FALSE FALSE
## 906 FALSE FALSE FALSE FALSE
## 907 FALSE FALSE FALSE FALSE
## 908 FALSE FALSE FALSE FALSE
## 909 FALSE FALSE FALSE FALSE
## 910 FALSE FALSE FALSE FALSE
## 911 FALSE FALSE FALSE FALSE
## 912 FALSE FALSE FALSE FALSE
## 913 FALSE FALSE FALSE FALSE
## 914 FALSE FALSE FALSE FALSE
## 915 FALSE FALSE FALSE FALSE
## 916 FALSE FALSE FALSE FALSE
## 917 FALSE FALSE FALSE FALSE
## 918 FALSE FALSE FALSE FALSE
## 919 FALSE FALSE FALSE FALSE
## 920 FALSE FALSE FALSE FALSE
## 921 FALSE FALSE FALSE FALSE
## 922 FALSE FALSE FALSE FALSE
## 923 FALSE FALSE FALSE FALSE
## 924 FALSE FALSE FALSE FALSE
## 925 FALSE FALSE FALSE FALSE
## 926 FALSE FALSE FALSE FALSE
## 927 FALSE FALSE FALSE FALSE
## 928 FALSE FALSE FALSE FALSE
## 929 FALSE FALSE FALSE FALSE
## 930 FALSE FALSE FALSE FALSE
## 931 FALSE FALSE FALSE FALSE
## 932 FALSE FALSE FALSE FALSE
## 933 FALSE FALSE FALSE FALSE
## 934 FALSE FALSE FALSE FALSE
## 935 FALSE FALSE FALSE FALSE
## 936 FALSE FALSE FALSE FALSE
## 937 FALSE FALSE FALSE FALSE
## 938 FALSE FALSE FALSE FALSE
## 939 FALSE FALSE FALSE FALSE
## 940 FALSE FALSE FALSE FALSE
## 941 FALSE FALSE FALSE FALSE
## 942 FALSE FALSE FALSE FALSE
## 943 FALSE FALSE FALSE FALSE
## 944 FALSE FALSE FALSE FALSE
## 945 FALSE FALSE FALSE FALSE
## 946 FALSE FALSE FALSE FALSE
## 947 FALSE FALSE FALSE FALSE
## 948 FALSE FALSE FALSE FALSE
## 949 FALSE FALSE FALSE FALSE
## 950 FALSE FALSE FALSE FALSE
## 951 FALSE FALSE FALSE FALSE
## 952 FALSE FALSE FALSE FALSE
## 953 FALSE FALSE FALSE FALSE
## 954 FALSE FALSE FALSE FALSE
## 955 FALSE FALSE FALSE FALSE
## 956 FALSE FALSE FALSE FALSE
## 957 FALSE FALSE FALSE FALSE
## 958 FALSE FALSE FALSE FALSE
## 959 FALSE FALSE FALSE FALSE
## 960 FALSE FALSE FALSE FALSE
## 961 FALSE FALSE FALSE FALSE
## 962 FALSE FALSE FALSE FALSE
## 963 FALSE FALSE FALSE FALSE
## 964 FALSE FALSE FALSE FALSE
## 965 FALSE FALSE FALSE FALSE
## 966 FALSE FALSE FALSE FALSE
## 967 FALSE FALSE FALSE FALSE
## 968 FALSE FALSE FALSE FALSE
## 969 FALSE FALSE FALSE FALSE
## 970 FALSE FALSE FALSE FALSE
## 971 FALSE FALSE FALSE FALSE
## 972 FALSE FALSE FALSE FALSE
## 973 FALSE FALSE FALSE FALSE
## 974 FALSE FALSE FALSE FALSE
## 975 FALSE FALSE FALSE FALSE
## 976 FALSE FALSE FALSE FALSE
## 977 FALSE FALSE FALSE FALSE
## 978 FALSE FALSE FALSE FALSE
## 979 FALSE FALSE FALSE FALSE
## 980 FALSE FALSE FALSE FALSE
## 981 FALSE FALSE FALSE FALSE
## 982 FALSE FALSE FALSE FALSE
## 983 FALSE FALSE FALSE FALSE
## 984 FALSE FALSE FALSE FALSE
## 985 FALSE FALSE FALSE FALSE
## 986 FALSE FALSE FALSE FALSE
## 987 FALSE FALSE TRUE FALSE
## 988 FALSE FALSE FALSE FALSE
## 989 FALSE FALSE FALSE FALSE
## 990 FALSE FALSE FALSE FALSE
## 991 FALSE FALSE FALSE FALSE
## 992 FALSE FALSE FALSE FALSE
## 993 FALSE FALSE FALSE FALSE
## 994 FALSE FALSE FALSE FALSE
## 995 FALSE FALSE FALSE FALSE
## 996 FALSE FALSE FALSE FALSE
## 997 FALSE FALSE FALSE FALSE
## 998 FALSE FALSE FALSE FALSE
## 999 FALSE FALSE FALSE FALSE
## 1000 FALSE FALSE FALSE FALSEsum(is.na(sklep_rowerowy))## [1] 0#Ze względu na bardzo małą liczbę braków danych zdecydowałyśmy się na imputacje metodą hot deck. Polega na zastępowaniu brakujących wartości (NA) rzeczywistymi wartościami pobranymi z podobnych obserwacji w tym samym zbiorze danych.
4 Wizualizacja danych
#Zależność wieku i zarobków
ggplot(sklep_rowerowy, aes(x=income,
y=age)) +
geom_point() +
xlab("Zarobek") +
ylab("Wiek")
ggtitle("Zarobki w porównaniu do wieku")## $title
## [1] "Zarobki w porównaniu do wieku"
##
## attr(,"class")
## [1] "labels"#Wniosek: Na podstawie wykresu można wywnioskować, że zarobek nie rośnie jednoznacznie z wiekiem. Dodatkowo osoby w podobnym wieku mają bardzo różne zarobki, choćby w przedziale 40 - 60 lat.Wszystko to może być zależne od branży czy wykształcenia badanej grupy osób. Większość zarobków znajduje się poniżej 100 000, co oznacza, że osoby zarabiające takie sumy są wyjątkiem. Zarobki powyżej 150 000 również są rzadkością.
Zależność pomiędzy liczbą dzieci a wiekiem
ggplot(sklep_rowerowy, aes(x=children,
y=age)) +
geom_point() +
xlab("Liczba dzieci") +
ylab("Wiek")
ggtitle("Zależność pomiędzy wiekiem, a liczbą dzieci")## $title
## [1] "Zależność pomiędzy wiekiem, a liczbą dzieci"
##
## attr(,"class")
## [1] "labels"#Wniosek: Dane są rozproszone, co pokazuje, że dzieci znajdują się w każdej grupie wiekowej. Najczęstszą obserwacją, w ogólnym rozkładzie wieku jest liczba dzieci: 2 i 3. Osoby w wieku poniżej 40 lat w zdecydowaniej większości nie posiadają dzieci lub pojawiają się one około 30 roku życia. Wyjątek można zauwazyć w pojedynczych przypadkach, choć przy 3 dzieci można zauważyć mocną tendencje wzrostową.
#Zależność pomiędzy posiadaniem domu a wiekiem
ggplot(sklep_rowerowy, aes(x=age,
y=home_owner)) +
geom_boxplot() +
xlab("Wiek") +
ylab("Posiadanie domu")
ggtitle("Posiadanie domu w porównaniu do wieku")## $title
## [1] "Posiadanie domu w porównaniu do wieku"
##
## attr(,"class")
## [1] "labels"#Wniosek: Osoby nie posiadające domu są w większości młodsze, ale widać też starsze osoby. Osoby posiadające dom są rozłożone bardziej równomiernie, ale dominują osoby w średnim i starszym wieku. Osoby starsze częściej są właścicielami domu co jest logiczne, ponieważ nieruchomość wymaga stabilizacji finansowej i czasu. Dodatkowo występuje kilka punktów odstających, które można zauważyć poza głównym obszarem wykresu - wśród posiadaczy domu są osoby powyżej 80 lat, ale pośród osoby bez domu również znadją się osoby w podeszłym wieku. Posiadanie domu rośnie z wiekiem, ponieważ ludzie oszczędzają przez lata i inwestują w nieruchomości.
#Zależność zarobków od poziomu edukacji
ggplot(sklep_rowerowy, aes(x=income,
y=education)) +
geom_boxplot() +
xlab("Zarobki") +
ylab("Poziom edukacji")
ggtitle("Zależność zarobków od poziomu edukacji")## $title
## [1] "Zależność zarobków od poziomu edukacji"
##
## attr(,"class")
## [1] "labels"#Poziom wykształcenia i wyjaśnienie Partial High School- częściowe wykształcenie średnie; Partial College - częściowe wykształcenie wyższe; High School - wykształcenie średnie; Graduate Degree - stopień magisterski; Bachelors - licencjat. #Wniosek: Grupy “Partial High School” i “Partial College” mają najniższe zarobki i najmniejsze zróżnicowanie. Z kolei osoby z tytułem licencjata mają naajwyższe zarobki, ale również najbardziej zróżnicowane. W każdej grupie można zauważyć punkty odstające, szczególnie w grupach z wyższym wykształceniem. Im wyższy poziom edukacji, tym wyższy poziom zarobków.
Zależność zarobków do posiadania rowerów
ggplot(sklep_rowerowy, aes(x=income,
y=purchased_bike)) +
geom_boxplot() +
xlab("Zarobki") +
ylab("Liczba rowerów")
ggtitle("Zależność zarobków do posiadania rowerów")## $title
## [1] "Zależność zarobków do posiadania rowerów"
##
## attr(,"class")
## [1] "labels"#Wniosek: Mediana zarobków osób z rowerem jest wyższa niż tych bez roweru. Rozkład zarobków dla obu grup ma podobny rozrzut, ale osoby z rowerem wydają się mieć wyższą medianę zarobków.
Wykres gęstości zarobków
ggplot(sklep_rowerowy, aes(x = income)) +
geom_density(alpha = 0.7, fill = "blue", color = "black") +
xlab("Zarobek") +
ylab("Gęstość") +
ggtitle("Rozkład zarobków") +
theme_minimal()
#Wniosek: Widać dwa wyraźne szczyty w okolicach 35 000 zł i 55 000 zł,
co sugeruje, że w badanej grupie występują dwie główne grupy zarobkowe.
Po 55 000 zł gęstość zaczyna maleć, ale nadal są osoby zarabiające ponad
100 000 zł. Przy najwyższych zarobkach (powyżej 150 000 zł) gęstość jest
bliska zeru, co oznacza, że bardzo niewiele osób osiąga tak wysokie
dochody.Nierównomierny rozkład wskazuje, że zarobki nie są symetrycznie
rozłożone – dominują dwa przedziały, a wysokie zarobki to rzadkość.
Grupowanie i zliczanie
library(dplyr)
dane_zliczone <- sklep_rowerowy %>%
group_by(region, purchased_bike) %>%
summarise(liczba = n(), .groups = "keep")#Liczba osób posiadających rowery w zależności od regionu
library(ggplot2)
ggplot(dane_zliczone, aes(x = "Region", y = liczba, fill = purchased_bike)) +
geom_bar(stat = "identity", position = "dodge") +
xlab("Region") +
ylab("Liczba osób") +
ggtitle("Liczba osób posiadających rowery w zależności od regionu") +
scale_fill_manual(values = c("Yes" = "blue", "No" = "red"), name = "Posiadanie roweru")
#Wniosek: Powyższy wykres przedstawia zależność posiadania rowerów od
zamieszkanego regionu. Najwięcej osób zamieszkuje północną Amerykę,
mniej w Europę i najmniej Pacyfik. W północnej Amreyce przeważa ilość
osob nie posiadających rowerów, nad ilością osób mających je. W Europie
ilość osób nie mających rowerów jest bardzo zbliżona, choć mininalnie
wyższa w porównaniu do ilości osób będących właścicielami rowerów. Na
Pacyfiku ilość osób będących w posiadaniu rowerów przeważa do tych,
którzy ich nie mają.
Grupowanie według wieku i posiadania roweru a następnie zliczanie
library(dplyr)
dane_wiek <- sklep_rowerowy %>%
group_by(age, purchased_bike) %>%
summarise(liczba = n(), .groups = "drop")#Zależność pomiędzy wiekiem a liczbą rowerów
library(ggplot2)
ggplot(dane_wiek, aes(x = age, y = liczba, fill = purchased_bike)) +
geom_bar(stat = "identity", position = "dodge") +
xlab("Wiek") +
ylab("Liczba osób") +
ggtitle("Liczba osób posiadających rowery w zależności od wieku") +
scale_fill_manual(values = c("Yes" = "green", "No" = "purple"), name = "Posiadanie roweru")
#Wniosek: Najwyższe słupki odzwierciedlają osoby w wieku około 36-38
lat, posiadające rowery. Zaś najwięcej osób nie mających rowerów
znajdują się w wieku 30 oraz 40. Jak widać, najwięcej jest na wykresie
osób młodych, w średnim wieku, aż po 70. Osób obserwowanych w wieku
70-80 lat jest najmniej, po 79 roku życia już według naszych danych,
nikt nie jest posiadaczem roweru.
Grupowanie i zliczanie według odległości dojazdu i posiadania roweru
library(dplyr)
dane_dojazd <- sklep_rowerowy %>%
group_by(commute_distance, purchased_bike) %>%
summarise(liczba = n(), .groups = "drop")Zależność pomiędzy posiadaniem roweru a odległością dojazdu do pracy
library(ggplot2)
library(forcats)
ggplot(dane_dojazd, aes(x = factor(commute_distance, levels = sort(unique(commute_distance))),
y = liczba, fill = purchased_bike)) +
geom_bar(stat = "identity", position = "stack") +
xlab("Odległość dojazdu do pracy") +
ylab("Liczba osób") +
ggtitle("Liczba osób posiadających rowery w zależności od odległości dojazdu do pracy") +
scale_fill_manual(values = c("Yes" = "yellow", "No" = "orange"), name = "Posiadanie roweru") +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) # Obrót etykiet dla lepszej czytelności
#Wniosek: Widać silną zależność pomiędzy posiadaniem roweru, a dystansem
do pracy. Najwięcej osób mieszka w odległości do pracy 0-1 mili, z
przewagą osób posiadających rowery. Choć jest też sporo osób w tym
dystansie do pracy nie posiadających rowerów. Te wyniki są za pewne
dlatego, ze zarówno łatwo jest dojechać do pracy rowerem tak krótki
odcinek jak i przejść się na pieszo. Najmniej osób mieszka w odległości
do pracy ponad 10 mili i w tym też więcej osób nie posiada rowerów, niż
posiada. Zapewne przy takim dystansie ludzie raczej już korzystają z
aut. Podobnie można zauważyć te tendencje w kategorii 5-10 mili
odległości do pracy- więcej osób w tej grupie, ale wciąż przeważa ilość
osób nie posiadająca rowery.
Zależność pomiędzy liczbą osób zamężnych a wiekiem
library(ggplot2)
library(hrbrthemes)
library(plotly)
library(ISLR) # for Credit data
data("Credit")
# Podziel zmienną Age na 3 przedziały wiekowe:
Credit$AgeGroup <- cut(Credit$Age, breaks=c(20,40,60,100),
labels=c("20-40", "40-60", "60-100"))
ggplot(Credit, aes(x=AgeGroup, fill=Married)) +
geom_bar(position="stack") +
labs(title="Liczba osób zamężnych w zależności od grupy wiekowej", x="Grupa wiekowa", y="Liczba osób") +
theme_classic()
#Wniosek: Dla każdej kategorii wiekowej jest więcej osób zamężnych, niż
singli. Słupki wraz z rosnącą grupą wiekową są coraz wyższe, co
wskazuje, że najwięcej osób oberwowanych jest w wieku 60-100 lat. Troche
mniej w 40-60 latach oraz najmniej w 20-40 latach.
Grupowanie i zliczanie
library(dplyr)
dane_zliczone <- sklep_rowerowy %>%
group_by(marital_status, purchased_bike) %>%
summarise(liczba = n(), .groups = "keep")#Zależność pomiędzy posiadaniem roweru a stanem cywilnym
library(ggplot2)
ggplot(dane_zliczone, aes(x = marital_status, y = liczba, fill = purchased_bike)) +
geom_bar(stat = "identity", position = "dodge") +
xlab("Stan cywilny") +
ylab("Liczba osób") +
ggtitle("Ilość osób posiadających rower w zależności od stanu cywilnego") +
scale_fill_manual(values = c("Yes" = "pink", "No" = "white"), name = "Posiadanie roweru")
#Wniosek: Na podstawie powyższego wykresu można wywnioskować, że więcej
osób obserwowanych jest w związku małżeńskim, zaś mniej singli.
Najwięcej osób znajduje się w kategorii zamężnych i nie posiadajacych
rowerów, jest tu prawie o 100 osób więcej niż singli nie posiadających
rowerów. Zaś właścicieli rowerów jest więcej wsród osób będących
singlami w porównaniu do osób zamężnych. Te wyniki prawdopodobnie
wynikają z tego, że osoby zamężne częściej korzystają z aut, aniżeli z
rowerów.
#Zależność pomiędzy posiadaniem roweru a płcią
library(dplyr)
library(ggplot2)
# Przygotowanie danych do wykresu kołowego
df_pie <- sklep_rowerowy %>%
group_by(gender, purchased_bike) %>%
summarise(count = n()) %>%
mutate(percentage = round(count / sum(count) * 100, 1)) # Zaokrąglamy do 1 miejsca## `summarise()` has grouped output by 'gender'. You can override using the
## `.groups` argument.# Tworzenie wykresu kołowego z etykietami procentowymi
ggplot(df_pie, aes(x = "", y = percentage, fill = purchased_bike)) +
geom_bar(stat = "identity", width = 1, color = "white") +
coord_polar("y", start = 0) + # Tworzymy wykres kołowy
facet_wrap(~gender) + # Oddzielne koła dla każdej płci
geom_text(aes(label = paste0(percentage, "%")), # Dodajemy procenty
position = position_stack(vjust = 0.5), size = 5, color = "white") +
labs(title = "Procent osób posiadających rower w podziale na płeć", fill = "Posiadanie roweru") +
scale_fill_manual(values = c("Yes" = "#2E86C1", "No" = "#A93226")) +
theme_void() # Usuwamy osie dla czystego wyglądu
#Wniosek: Jak widać płeć nie ma szczególnej zależności w zakresie
posiadania roweru. Wyniki na obu wykresach wyszły bardzo podobnie. Jest
minimalna przewaga mężczyzn będąca właścicielami rowerów w porównaniu do
ilości kobiet posiadająca rowery. Zaś odrobinę więcej kobiet nie ma
rowerów w zestawieniu do mężczyzn.
#Zależność między posiadaniem roweru i posiadaniem dzieci
library(ggplot2)
library(hrbrthemes)
ggplot(sklep_rowerowy, aes(x = factor(children), fill = purchased_bike)) +
geom_bar(position = "dodge", width = 0.6) +
labs(title = "Posiadanie roweru w zależności od liczby dzieci",
x = "Liczba dzieci", y = "Liczba osób") +
scale_fill_manual(values = c("Yes" = "#00BFC4", "No" = "#F8766D"),
name = "Posiadanie roweru") +
theme_minimal(base_size = 14)
#Wniosek: Powyższy wykres wyraźnie pokazuje, że im mniej dzieci, tym
więcej osób jest w posiadaniu rowerów. Widać też, że najwięcej osób
wśród obserwowanych nie ma dzieci, tam też ilości osób posiadających i
nie posiadających rowery są na zbliżonym poziomie. Najmniejsza liczba
osób mająca rowery jest równocześnie rodzicem 5 dzieci.
#Zależność pomiędzy poiadaniem roweru a poziomem wykształcenia
library(dplyr)
# Przygotowanie danych do wykresu kołowego
df_pie <- sklep_rowerowy %>%
group_by(education, purchased_bike) %>%
summarise(count = n()) %>%
mutate(percentage = round(count / sum(count) * 100, 1)) # Zaokrąglamy do 1 miejsca## `summarise()` has grouped output by 'education'. You can override using the
## `.groups` argument.# Tworzenie wykresu kołowego z etykietami procentowymi
ggplot(df_pie, aes(x = "", y = percentage, fill = purchased_bike)) +
geom_bar(stat = "identity", width = 1, color = "white") +
coord_polar("y", start = 0) + # Tworzymy wykres kołowy
facet_wrap(~education) + # Osobne koła dla każdej grupy edukacyjnej
geom_text(aes(label = paste0(percentage, "%")),
position = position_stack(vjust = 0.5), size = 5, color = "white") +
labs(title = "Procent osób posiadających rower w zależności od poziomu edukacji",
fill = "Czy posiada rower?") +
scale_fill_manual(values = c("Yes" = "gray", "No" = "purple")) +
theme_void() +
theme(strip.text = element_text(size = 12, face = "bold")) # Lepsza czytelność
#Wniosek: Na podstawie powyższego wykresu widać, że poziom edukacji ma
wyrażny wpływ na bycie właścicielem rowery bądź nie. Najmniej osób ma
rower w kategorii Partial High School, liczy to prawie 74%. Wraz ze
wzrostem edukacji te wyniki posiadania lub nie posiadania roweru
oscylują wokoł około 44%-56%, a więc są bliskie połowy. Najwięcej osób
są właścicielami rowerów z poziomem edukacji Bachelors.
#Zależność pomiędzy posiadaniem roweru vs zawodem
library(ggplot2)
library(dplyr)
if(!require("ggmosaic")) install.packages("ggmosaic") ## Ładowanie wymaganego pakietu: ggmosaic## Warning: pakiet 'ggmosaic' został zbudowany w wersji R 4.4.2library(ggmosaic)
# Dla wykresu mozaikowego
ggplot(sklep_rowerowy, aes(x = occupation, fill = purchased_bike)) +
geom_bar(position = "dodge") +
scale_fill_manual(values = c("Yes" = "salmon", "No" = "white")) + # Zmiana kolorów
labs(title = "Ilość osób posiadających rower w zależności od zawodu",
x = "Zawód",
y = "Liczba osób",
fill = "Posiadanie roweru") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
#Wniosek: Największe grupy osób nie posiadających rowerów znajdują się w
kategoriach zawodu Professional i Skilled manual. Tam również są
najwyższe ilości osób mające rowery, z przewagą dla zawodu professional.
Najmniejsze ilości osób posiadajacych i nieposiadających rowery znajdują
się w kategorii zawodu manual.
#Zależność między posiadaniem roweru vs posiadaniem domu
library(ggplot2)
library(dplyr)
ggplot(sklep_rowerowy, aes(x = home_owner, fill = purchased_bike)) +
geom_bar(position = "fill") +
scale_y_continuous(labels = scales::percent) +
scale_fill_manual(values = c("Yes" = "darkgreen", "No" = "lightblue")) + # Zmiana kolorów
labs(title = "Procent osób mających rower w zalezności od posiadania domu",
x = "Posiadanie domu",
y = "Procent",
fill = "Posiadanie roweru") +
theme_minimal()
#Wniosek: Można zaobserwować na podstawie powyższego wykresu, że
posiadanie roweru nie jest za bardzo uzależnione od posiadania domu lub
jego braku. W obu słupkach minimalnie przeważa nie posiadanie roweru dla
obu opcji. Dla właścicieli domów jest odrobinę mniej osób posiadających
rowery w porównaniu do ludzi, którzy tego domu nie mają.
#Zależność między posiadaniem roweru vs posiadaniem auta
library(ggplot2)
library(hrbrthemes)
ggplot(sklep_rowerowy, aes(x = factor(cars), fill = purchased_bike)) +
geom_bar(position = "dodge", width = 0.6) +
labs(title = "Zależność między posiadaniem roweru, a ilością aut",
x = "Liczba aut", y = "Liczba osób") +
scale_fill_manual(values = c("Yes" = "#00BFC4", "No" = "#F8766D"),
name = "Posiadanie roweru") +
theme_minimal(base_size = 14)
#Wniosek: Na podstawie wykresu można zauważyć, że wraz ze wzrostem
liczby samochodów w gospodarstwie domowym maleje prawdopodobieństwo
posiadania roweru. Najwięcej osób posiadających rowery znajduje się w
grupach posiadających 0–2 samochody. Z kolei największa liczba osób,
które nie posiadają roweru (około 220), to właściciele dwóch aut.
Test t-Studenta: różnice w dochodach w zależności od zakupu roweru
sklep_rowerowy <- sklep_rowerowy %>% filter(!is.na(income), !is.na(purchased_bike))
t_test_result <- t.test(income ~ purchased_bike, data = sklep_rowerowy)
print(t_test_result)##
## Welch Two Sample t-test
##
## data: income by purchased_bike
## t = -1.4788, df = 993.51, p-value = 0.1395
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
## -6750.0213 948.6041
## sample estimates:
## mean in group No mean in group Yes
## 54874.76 57775.47if (t_test_result$p.value < 0.05) {
print("Istnieje statystycznie istotna różnica w dochodach między osobami, które kupiły rower, a tymi, które go nie kupiły.")
} else {
print("Nie stwierdzono istotnej różnicy w dochodach między osobami, które kupiły rower, a tymi, które go nie kupiły.")
}## [1] "Nie stwierdzono istotnej różnicy w dochodach między osobami, które kupiły rower, a tymi, które go nie kupiły."Test chi-kwadrat: zależność między płcią a zakupem roweru
gender_bike_table <- table(sklep_rowerowy$gender, sklep_rowerowy$purchased_bike)
chi_sq_result <- chisq.test(gender_bike_table)
print(chi_sq_result)##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: gender_bike_table
## X-squared = 0.18168, df = 1, p-value = 0.6699if (chi_sq_result$p.value < 0.05) {
print("Istnieje statystycznie istotna zależność między płcią a zakupem roweru.")
} else {
print("Nie stwierdzono istotnej zależności między płcią a zakupem roweru.")
}## [1] "Nie stwierdzono istotnej zależności między płcią a zakupem roweru."ANOVA: różnice wieku w zależności od poziomu wykształcenia
anova_result <- aov(age ~ education, data = sklep_rowerowy)
summary(anova_result)## Df Sum Sq Mean Sq F value Pr(>F)
## education 4 1142 285.5 2.23 0.0639 .
## Residuals 995 127402 128.0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Istnieje statystycznie istotna różnica w średnim wieku w zależności od poziomu wykształcenia na poziomie 10%.
5. Wnioskowanie statystyczne projektu
Analiza struktury danych: Pierwszym krokiem było sprawdzenie struktury zbioru danych. Dane składają się z różnych cech demograficznych i ekonomicznych klientów, takich jak wiek, dochód, liczba dzieci, wykształcenie, czy posiadanie domu. Kolumny zawierają zarówno zmienne numeryczne, jak i kategoryczne.
Analiza braków danych: Stwierdzono 53 braki w zbiorze danych, co stanowi około 0,41% wszystkich wartości.Najwięcej braków dotyczyło zmiennej Gender(płeć) oraz cech związanych z edukacją, dochodami i stanowiskiem pracy. Przeprowadzono wizualizację braków, wskazując ich rozkład w poszczególnych kolumnach.
Walidacja danych
#W celu weryfikacji poprawności danych zastosowano reguły: wiek w przedziale 1-120 lat;dochód większy lub równy 0; liczba dzieci w przedziale 0-5;liczba samochodów w przedziale 0-10; sprawdzono zależności między zmiennymi np. “Marital.status == Married” oraz “Income >= 70000”; zweryfikowano także zgodność pomiędzy poziomem edukacji a stanowiskiem pracy.
Imputacja brakujących wartości: ze względu na niewielką liczbę braków zdecydowano się na imputację metodą hot deck. Jest to metoda polegająca na uzupełnianiu braków wartościami z podobnych obserwacji. Po imputacji zweryfikowano brakujące wartości – nie wystąpiły żadne brakujące dane po uzupełnieniu.
Wizualizacja danych i wnioski
#Krótkie przypomnienie paru wykresów, ponieważ każdy został wcześniej zinterpretowany.